2001 LearningWithKernels

(Schölkopf & Smola, 2001) ⇒ Bernhard Schölkopf, and Alexander J. Smola. (2001). “Learning With Kernels: Support Vector Machines, Regularization, Optimization, and Beyond." MIT Press. ISBN:0262194759

Subject Headings: Support Vector Machine Classifier, Kernel Function.

Notes

Cited By

2004

(Hastie et al., 2004) ⇒ Trevor Hastie, Saharon Rosset, Robert Tibshirani, and Ji Zhu. (2004). “The Entire Regularization Path for the Support Vector Machine." In: The Journal of Machine Learning Research, 5.

Quotes

Book Overview

In the 1990s, a new type of learning algorithm was developed, based on results from statistical learning theory: the Support Vector Machine (SVM). This gave rise to a new class of theoretically elegant learning machines that use a central concept of SVMs -- kernels -- for a number of learning tasks. Kernel machines provide a modular framework that can be adapted to different tasks and domains by the choice of the kernel function and the base algorithm. They are replacing neural networks in a variety of fields, including engineering, information retrieval, and bioinformatics.

Learning with Kernels provides an introduction to SVMs and related kernel methods. Although the book begins with the basics, it also includes the latest research. It provides all of the concepts necessary to enable a reader equipped with some basic mathematical knowledge to enter the world of machine learning using theoretically well-founded yet easy-to-use kernel algorithms and to understand and apply the powerful algorithms that have been developed over the last few years.

1 A Tutorial Introduction

1.1  Data Representation and Similarity . . . . . . . . . . . . . . . . . . .   1
1.2  A Simple Pattern Recognition Algorithm  . . . . . . . . . . . . . . .   3
1.3  Some Insights From Statistical Learning Theory . . . . . . . . . . . .   6
1.4  Hyperplane Classifiers . . . . . . . . . . . . . . . . . . . . . . . . . .  10
1.5  Support Vector Classification . . . . . . . . . . . . . . . . . . . . . . 13
1.6  Support Vector Regression . . . . . . . . . . . . . . . . . . . . . . . .  16
1.7  Kernel Principal Component Analysis  . . . . . . . . . . . . . . . . .  18
1.8  Empirical Results and Implementations  . . . . . . . . . . . . . . . .  19

…

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130. Rui Li, Bir Bhanu, Anlei Dong, Coevolutionary Feature Synthesized EM Algorithm for Image Retrieval, Proceedings of the 13th Annual ACM International Conference on Multimedia, November 06-11, 2005, Hilton, Singapore
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159. Jun Hua Zhao, Zhao Yang Dong, Pei Zhang, Mining Complex Power Networks for Blackout Prevention, Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, August 12-15, 2007, San Jose, California, USA
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165. Julian Szymański, Włodzisław Duch, Representation of Hypertext Documents based on Terms, Links and Text Compressibility, Proceedings of the 17th International Conference on Neural Information Processing: Theory and Algorithms, November 22-25, 2010, Sydney, Australia
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173. Derek Greene, Pádraig Cunningham, Practical Solutions to the Problem of Diagonal Dominance in Kernel Document Clustering, Proceedings of the 23rd International Conference on Machine Learning, p.377-384, June 25-29, 2006, Pittsburgh, Pennsylvania
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177. Konstantin Böttinger, Dieter Schuster, Claudia Eckert, Detecting Fingerprinted Data in TLS Traffic, Proceedings of the 10th ACM Symposium on Information, Computer and Communications Security, April 14-March 17, 2015, Singapore, Republic of Singapore
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191. Thomas Stibor, An Empirical Study of Self/Non-self Discrimination in Binary Data with a Kernel Estimator, Proceedings of the 7th International Conference on Artificial Immune Systems, August 10-13, 2008, Phuket, Tailand
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196. Murat Aykut, Murat Ekinci, Kernel Principal Component Analysis of Gabor Features for Palmprint Recognition, Proceedings of the Third International Conference on Advances in Biometrics, June 02-05, 2009, Alghero, Italy
197. Yale Song, Louis-Philippe Morency, Randall Davis, Multimodal Human Behavior Analysis: Learning Correlation and Interaction Across Modalities, Proceedings of the 14th ACM International Conference on Multimodal Interaction, October 22-26, 2012, Santa Monica, California, USA
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250. João Carreira, Paulo Peixoto, Nuisance Free Recognition of Hand Postures over a Tabletop Display, Proceedings of the HCSNet Workshop on Use of Vision in Human-computer Interaction, p.73-78, November 01-01, 2006, Canberra, Australia
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253. Lingzhi Wang, Jiansheng Wu, Neural Network Ensemble Model Using PPR and LS-SVR for Stock Market Forecasting, Proceedings of the 7th International Conference on Advanced Intelligent Computing, August 11-14, 2011, Zhengzhou, China
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259. Alfio Gliozzo, Carlo Strapparava, Domain Kernels for Text Categorization, Proceedings of the Ninth Conference on Computational Natural Language Learning, June 29-30, 2005, Ann Arbor, Michigan
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265. Ziheng Zhou, Samuel Chindaro, Farzin Deravi, A Classification Framework for Large-Scale Face Recognition Systems, Proceedings of the Third International Conference on Advances in Biometrics, June 02-05, 2009, Alghero, Italy
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267. Sebastian Bothe, Thomas Gärtner, Stefan Wrobel, On-line Handwriting Recognition with Parallelized Machine Learning Algorithms, Proceedings of the 33rd Annual German Conference on Advances in Artificial Intelligence, September 21-24, 2010, Karlsruhe, Germany
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280. Sepp Hochreiter, Klaus Obermayer, Feature Selection and Classification on Matrix Data: From Large Margins to Small Covering Numbers, Proceedings of the 15th International Conference on Neural Information Processing Systems, p.913-920, January 01, 2002
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287. Adam Kowalczyk, Olivier Chapelle, An Analysis of the Anti-learning Phenomenon for the Class Symmetric Polyhedron, Proceedings of the 16th International Conference on Algorithmic Learning Theory, October 08-11, 2005, Singapore
288. Chi-Man Vong, Pak-Kin Wong, Yi-Ping Li, Prediction of Automotive Engine Power and Torque Using Least Squares Support Vector Machines and Bayesian Inference, Engineering Applications of Artificial Intelligence, v.19 n.3, p.277-287, April, 2006
289. Ola Amayri, Nizar Bouguila, Improved Online Support Vector Machines Spam Filtering Using String Kernels, Proceedings of the 14th Iberoamerican Conference on Pattern Recognition: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, November 15-18, 2009, Guadalajara, Jalisco, Mexico
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291. Sinno Jialin Pan, James T. Kwok, Qiang Yang, Jeffrey Junfeng Pan, Adaptive Localization in a Dynamic WiFi Environment through Multi-view Learning, Proceedings of the 22nd National Conference on Artificial Intelligence, p.1108-1113, July 22-26, 2007, Vancouver, British Columbia, Canada
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293. José Alí Moreno, Cristina García, Robot Path Planning in Kernel Space, Proceedings of the 8th International Conference on Adaptive and Natural Computing Algorithms, Part II, April 11-14, 2007, Warsaw, Poland
294. Jaume Gibert, Ernest Valveny, Horst Bunke, Graph of Words Embedding for Molecular Structure-activity Relationship Analysis, Proceedings of the 15th Iberoamerican Congress Conference on Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, November 08-11, 2010, São Paulo, Brazil
295. Thomas Stibor, A Study of Detecting Computer Viruses in Real-infected Files in the N-gram Representation with Machine Learning Methods, Proceedings of the 23rd International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, June 01-04, 2010, Cordoba, Spain
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310. Andrew Cotter, Nathan Srebro, Joseph Keshet, A GPU-tailored Approach for Training Kernelized SVMs, Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, August 21-24, 2011, San Diego, California, USA
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314. Shiliang Sun, A Theoretical Derivation of the Kernel Extreme Energy Ratio Method for EEG Feature Extraction, Proceedings of the 9th International Conference on Intelligent Data Engineering and Automated Learning, November 02-05, 2008, Daejeon, South Korea
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321. Michael Donoser, Silke Wagner, Horst Bischof, Context Information from Search Engines for Document Recognition, Pattern Recognition Letters, v.31 n.8, p.750-754, June, 2010
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334. Behnam Babagholami-Mohamadabadi, Ali Zarghami, Hojjat Abdollahi Pourhaghighi, Mohammad T. Manzuri-Shalmani, Probabilistic Non-linear Distance Metric Learning for Constrained Clustering, Proceedings of the 4th MultiClust Workshop on Multiple Clusterings, Multi-view Data, and Multi-source Knowledge-driven Clustering, p.1-8, August 11-14, 2013, Chicago, Illinois
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336. Ricardo Ñanculef, Héctor Allende, Stefano Lodi, Claudio Sartori, Two One-pass Algorithms for Data Stream Classification Using Approximate MEBs, Proceedings of the 10th International Conference on Adaptive and Natural Computing Algorithms, April 14-16, 2011, Ljubljana, Slovenia
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339. Altaf Hossain, Faisal Zaman, M. Nasser, M. Mufakhkharul Islam, Comparison of GARCH, Neural Network and Support Vector Machine in Financial Time Series Prediction, Proceedings of the 3rd International Conference on Pattern Recognition and Machine Intelligence, December 16-20, 2009, New Delhi, India
340. Weibing Chen, Hongxia Yin, Yingjie Tian, Smoothing Newton Method for L1 Soft Margin Data Classification Problem, Proceedings of the 9th International Conference on Computational Science, May 25-27, 2009, Baton Rouge, LA, USA
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349. Valentin Schwamberger, Matthias O. Franz, Simple Algorithmic Modifications for Improving Blind Steganalysis Performance, Proceedings of the 12th ACM Workshop on Multimedia and Security, September 09-10, 2010, Roma, Italy
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510. Ninh Pham, Rasmus Pagh, Fast and Scalable Polynomial Kernels via Explicit Feature Maps, Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, August 11-14, 2013, Chicago, Illinois, USA
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517. Chao Liu, Yi-Min Wang, On the Connections Between Explicit Semantic Analysis and Latent Semantic Analysis, Proceedings of the 21st ACM International Conference on Information and Knowledge Management, October 29-November 02, 2012, Maui, Hawaii, USA
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537. Chan-Su Lee, Ahmed Elgammal, Dimitris Metaxas, Nonlinear Dynamic Shape and Appearance Models for Facial Motion Tracking, Proceedings of the 2nd Pacific Rim Conference on Advances in Image and Video Technology, December 17-19, 2007, Santiago, Chile
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545. Sébastien Lahaie, Stability and Incentive Compatibility in a Kernel-based Combinatorial Auction, Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence, p.811-816, July 11-15, 2010, Atlanta, Georgia
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589. Mohammad Ali Bagheri, Qigang Gao, Sergio Escalera, Action Recognition by Pairwise Proximity Function Support Vector Machines with Dynamic Time Warping Kernels, Proceedings of the 29th Canadian Conference on Artificial Intelligence on Advances in Artificial Intelligence, May 31-June 03, 2016
590. Alexander Grubb, J. Andrew Bagnell, Boosted Backpropagation Learning for Training Deep Modular Networks, Proceedings of the 27th International Conference on International Conference on Machine Learning, p.407-414, June 21-24, 2010, Haifa, Israel
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598. D. Sculley, Practical Learning from One-sided Feedback, Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, August 12-15, 2007, San Jose, California, USA
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606. Klaus Brinker, Active Learning of Label Ranking Functions, Proceedings of the Twenty-first International Conference on Machine Learning, p.17, July 04-08, 2004, Banff, Alberta, Canada
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660. Raouia Ayachi, Nahla Ben Amor, Brain Tumor Segmentation Using Support Vector Machines, Proceedings of the 10th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty, July 01-03, 2009, Verona, Italy
661. Wittawat Jitkrittum, Arthur Gretton, Nicolas Heess, S. M. Ali Eslami, Balaji Lakshminarayanan, Dino Sejdinovic, Zoltán Szabó, Kernel-based Just-In-Time Learning for Passing Expectation Propagation Messages, Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, July 12-16, 2015, Amsterdam, Netherlands
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675. Tansu Alpcan, A Framework for Optimization under Limited Information, Proceedings of the 5th International ICST Conference on Performance Evaluation Methodologies and Tools, May 16-20, 2011, Paris, France
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677. Chan-Su Lee, Ahmed Elgammal, Homeomorphic Manifold Analysis: Learning Decomposable Generative Models for Human Motion Analysis, Proceedings of the 2005/2006 International Conference on Dynamical Vision, May 13, 2006, Graz, Austria
678. Mehmet Gönen, Embedding Heterogeneous Data by Preserving Multiple Kernels, Proceedings of the Twenty-first European Conference on Artificial Intelligence, August 18-22, 2014, Prague, Czech Republic
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683. Marco Cuturi, Permanents, Transport Polytopes and Positive Definite Kernels on Histograms, Proceedings of the 20th International Joint Conference on Artifical Intelligence, p.732-737, January 06-12, 2007, Hyderabad, India
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706. Leonardo Barros Nascimento, Anselmo Cardoso De Paiva, Aristófanes Corrêa Silva, Lung Nodules Classification in CT Images Using Shannon and Simpson Diversity Indices and SVM, Proceedings of the 8th International Conference on Machine Learning and Data Mining in Pattern Recognition, July 13-20, 2012, Berlin, Germany
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711. S. Deng, Tsung-Han Yeh, Applying Least Squares Support Vector Machines to the Airframe Wing-box Structural Design Cost Estimation, Expert Systems with Applications: An International Journal, v.37 n.12, p.8417-8423, December, 2010
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714. Karim Gasmi, Ahmed Kharrat, Mohamed Ben Messaoud, Mohamed Abid, Automated Segmentation of Brain Tumor Using Optimal Texture Features and Support Vector Machine Classifier, Proceedings of the 9th International Conference on Image Analysis and Recognition, June 25-27, 2012, Aveiro, Portugal
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719. Zhixiang Xu, Gao Huang, Kilian Q. Weinberger, Alice X. Zheng, Gradient Boosted Feature Selection, Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, August 24-27, 2014, New York, New York, USA
720. Leting Pan, Human Age Estimation by Metric Learning for Regression Problems, Proceedings of the 7th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition, August 24-27, 2009, Bonn, Germany
721. P. J. García Nieto, E. F. Combarro, J. J. Del Coz Díaz, E. Montañés, A SVM-based Regression Model to Study the Air Quality at Local Scale in Oviedo Urban Area (Northern Spain): A Case Study, Applied Mathematics and Computation, v.219 n.17, p.8923-8937, May, 2013
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724. Na Chen, Qian-Yi Zhou, Viktor Prasanna, Understanding Web Images by Object Relation Network, Proceedings of the 21st International Conference on World Wide Web, April 16-20, 2012, Lyon, France
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726. Nicola Segata, Enrico Blanzieri, Fast Local Support Vector Machines for Large Datasets, Proceedings of the 6th International Conference on Machine Learning and Data Mining in Pattern Recognition, July 23-25, 2009, Leipzig, Germany
727. Hastagiri P. Vanchinathan, Isidor Nikolic, Fabio De Bona, Andreas Krause, Explore-exploit in Top-N Recommender Systems via Gaussian Processes, Proceedings of the 8th ACM Conference on Recommender Systems, October 06-10, 2014, Foster City, Silicon Valley, California, USA
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729. Sébastien Bratières, Novi Quadrianto, Sebastian Nowozin, Zoubin Ghahramani, Scalable Gaussian Process Structured Prediction for Grid Factor Graph Applications, Proceedings of the 31st International Conference on International Conference on Machine Learning, June 21-26, 2014, Beijing, China
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732. Min-Ling Zhang, Bin-Bin Zhou, Xu-Ying Liu, Partial Label Learning via Feature-Aware Disambiguation, Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, August 13-17, 2016, San Francisco, California, USA
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738. Gang Wu, Edward Y. Chang, Navneet Panda, Formulating Context-dependent Similarity Functions, Proceedings of the 13th Annual ACM International Conference on Multimedia, November 06-11, 2005, Hilton, Singapore
739. Koby Crammer, Tal Wagner, Volume Regularization for Binary Classification, Proceedings of the 25th International Conference on Neural Information Processing Systems, p.332-340, December 03-06, 2012, Lake Tahoe, Nevada
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745. Christian Igel, Tobias Glasmachers, Britta Mersch, Nico Pfeifer, Peter Meinicke, Gradient-Based Optimization of Kernel-Target Alignment for Sequence Kernels Applied to Bacterial Gene Start Detection, IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), v.4 n.2, p.216-226, April 2007
746. Keng-Pei Lin, Ming-Syan Chen, Privacy-preserving Outsourcing Support Vector Machines with Random Transformation, Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, July 25-28, 2010, Washington, DC, USA
747. Arthur Tenenhaus, Alain Giron, Emmanuel Viennet, Michel Béra, Gilbert Saporta, Bernard Fertil, Kernel Logistic PLS: A Tool for Supervised Nonlinear Dimensionality Reduction and Binary Classification, Computational Statistics & Data Analysis, v.51 n.9, p.4083-4100, May, 2007
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750. Nicolas Couellan, Wenjuan Wang, Uncertainty-safe Large Scale Support Vector Machines, Computational Statistics & Data Analysis, v.109 N.C, p.215-230, May 2017
751. Luis Rueda, B. John Oommen, Claudio Henríquez, Multi-class Pairwise Linear Dimensionality Reduction Using Heteroscedastic Schemes, Pattern Recognition, v.43 n.7, p.2456-2465, July, 2010
752. Ichigaku Takigawa, Mineichi Kudo, Atsuyoshi Nakamura, Convex Sets As Prototypes for Classifying Patterns, Engineering Applications of Artificial Intelligence, v.22 n.1, p.101-108, February, 2009
753. Wolfgang Konen, Patrick Koch, Oliver Flasch, Thomas Bartz-Beielstein, Martina Friese, Boris Naujoks, Tuned Data Mining: A Benchmark Study on Different Tuners, Proceedings of the 13th Annual Conference on Genetic and Evolutionary Computation, July 12-16, 2011, Dublin, Ireland
754. Ying Zhao, Justin Zobel, Entropy-based Authorship Search in Large Document Collections, Proceedings of the 29th European Conference on IR Research, April 02-05, 2007, Rome, Italy
755. Shai Shalev-Shwartz, Ohad Shamir, Karthik Sridharan, Learning Kernel-Based Halfspaces with the 0-1 Loss, SIAM Journal on Computing, v.40 n.6, p.1623-1646, November 2011
756. J. Farquhar, 2009 Special Issue: A Linear Feature Space for Simultaneous Learning of Spatio-spectral Filters in BCI, Neural Networks, v.22 n.9, p.1278-1285, November, 2009
757. Carlotta Orsenigo, Carlo Vercellis, Time Series Gene Expression Data Classification via L<inf>1</inf>-norm Temporal SVM, Proceedings of the 5th IAPR International Conference on Pattern Recognition in Bioinformatics, September 22-24, 2010, Nijmegen, The Netherlands
758. Hongfang Liu, Manabu Torii, Guixian Xu, Zhangzhi Hu, Johannes Goll, Learning from Positive and Unlabeled Documents for Retrieval of Bacterial Protein-protein Interaction Literature, Proceedings of the 2009 Workshop of the BioLink Special Interest Group, International Conference on Linking Literature, Information, and Knowledge for Biology, June 28-29, 2009, Stockholm
759. Bernhard Moser, Gernot Stübl, Jean-Luc Bouchot, On a Non-monotonicity Effect of Similarity Measures, Proceedings of the First International Conference on Similarity-based Pattern Recognition, September 28-30, 2011, Venice, Italy
760. Emanuele Olivetti, Paolo Avesani, Supervised Segmentation of Fiber Tracts, Proceedings of the First International Conference on Similarity-based Pattern Recognition, September 28-30, 2011, Venice, Italy
761. Francisco S. Melo, Manuel Lopes, Learning from Demonstration Using MDP Induced Metrics, Proceedings of the 2010 European Conference on Machine Learning and Knowledge Discovery in Databases: Part II, September 20-24, 2010, Barcelona, Spain
762. Matthieu Solnon, Sylvain Arlot, Francis Bach, Multi-task Regression Using Minimal Penalties, The Journal of Machine Learning Research, v.13 n.1, p.2773-2812, January 2012
763. Subhabrata Choudhury, Subhajyoti Ghosh, Arnab Bhattacharya, Kiran Jude Fernandes, Manoj Kumar Tiwari, A Real Time Clustering and SVM based Price-volatility Prediction for Optimal Trading Strategy, Neurocomputing, 131, p.419-426, May, 2014
764. Zhixiang Xu, Matt J. Kusner, Kilian Q. Weinberger, Minmin Chen, Cost-sensitive Tree of Classifiers, Proceedings of the 30th International Conference on International Conference on Machine Learning, June 16-21, 2013, Atlanta, GA, USA
765. Yan-Fu Liu, Cheng-Yu Hsu, Shan-Hung Wu, Non-linear Cross-domain Collaborative Filtering via Hyper-structure Transfer, Proceedings of the 32nd International Conference on International Conference on Machine Learning, July 06-11, 2015, Lille, France
766. Xiang-Yang Wang, Xian-Jin Zhang, Hong-Ying Yang, Juan Bu, A Pixel-based Color Image Segmentation Using Support Vector Machine and Fuzzy C-means, Neural Networks, 33, p.148-159, September, 2012
767. Chen Jing, Jian Hou, SVM and PCA based Fault Classification Approaches for Complicated Industrial Process, Neurocomputing, v.167 N.C, p.636-642, November 2015
768. Yuhong Guo, Dale Schuurmans, Multi-label Classification with Output Kernels, Proceedings, Part II, of the European Conference on Machine Learning and Knowledge Discovery in Databases, September 23-27, 2013, Prague, Czech Republic
769. Ryan Turner, Steven Bottone, Bhargav Avasarala, A Complete Variational Tracker, Proceedings of the 27th International Conference on Neural Information Processing Systems, p.496-504, December 08-13, 2014, Montreal, Canada
770. Liang Sun, Betul Ceran, Jieping Ye, A Scalable Two-stage Approach for a Class of Dimensionality Reduction Techniques, Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, July 25-28, 2010, Washington, DC, USA
771. Josip Djolonga, Andreas Krause, Volkan Cevher, High-dimensional Gaussian Process Bandits, Proceedings of the 26th International Conference on Neural Information Processing Systems, p.1025-1033, December 05-10, 2013, Lake Tahoe, Nevada
772. Justin Ma, Lawrence K. Saul, Stefan Savage, Geoffrey M. Voelker, Beyond Blacklists: Learning to Detect Malicious Web Sites from Suspicious URLs, Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, June 28-July 01, 2009, Paris, France
773. Jun Zhu, Ning Chen, Eric P. Xing, Infinite SVM: A Dirichlet Process Mixture of Large-margin Kernel Machines, Proceedings of the 28th International Conference on International Conference on Machine Learning, p.617-624, June 28-July 02, 2011, Bellevue, Washington, USA
774. Michael Fink, Shimon Ullman, From Aardvark to Zorro: A Benchmark for Mammal Image Classification, International Journal of Computer Vision, v.77 n.1-3, p.143-156, May 2008
775. Eyke Hüllermeier, Klaus Brinker, Learning Valued Preference Structures for Solving Classification Problems, Fuzzy Sets and Systems, v.159 n.18, p.2337-2352, September, 2008
776. Tsuneyoshi Ishii, Masamichi Ashihara, Shigeo Abe, Kernel Discriminant Analysis based Feature Selection, Neurocomputing, v.71 n.13-15, p.2544-2552, August, 2008
777. Bhavani Raskutti, Adam Kowalczyk, Extreme Re-balancing for SVMs: A Case Study, ACM SIGKDD Explorations Newsletter, v.6 n.1, June 2004
778. Abdulrahman Alenezi, Scott A. Moses, Theodore B. Trafalis, Real-time Prediction of Order Flowtimes Using Support Vector Regression, Computers and Operations Research, v.35 n.11, p.3489-3503, November, 2008
779. Chunyuan Zhang, Qingxin Zhu, Xinzheng Niu, Kernel Recursive Least-Squares Temporal Difference Algorithms with Sparsification and Regularization, Computational Intelligence and Neuroscience, 2016, p.4, June 2016
780. Ginés Rubio, Luis Javier Herrera, Héctor Pomares, Ignacio Rojas, Alberto Guillén, Design of Specific-to-problem Kernels and Use of Kernel Weighted K-nearest Neighbours for Time Series Modelling, Neurocomputing, v.73 n.10-12, p.1965-1975, June, 2010
781. Zhiqiang Ge, Zhihuan Song, A Distribution-free Method for Process Monitoring, Expert Systems with Applications: An International Journal, v.38 n.8, p.9821-9829, August, 2011
782. Murat Ekinci, Murat Aykut, Improved Gait Recognition by Multiple-projections Normalization, Machine Vision and Applications, v.21 n.2, p.143-161, February 2010
783. Rob Fergus, Hector Bernal, Yair Weiss, Antonio Torralba, Semantic Label Sharing for Learning with Many Categories, Proceedings of the 11th European Conference on Computer Vision: Part I, September 05-11, 2010, Heraklion, Crete, Greece
784. Cleriston Araujo Silva, Aristófanes Corrêa Silva, Stelmo Magalhães Netto, Anselmo Cardoso Paiva, Geraldo Braz Junior, Rodolfo Acatauassú Nunes, Lung Nodules Classification in CT Images Using Simpson's Index, Geometrical Measures and One-Class SVM, Proceedings of the 6th International Conference on Machine Learning and Data Mining in Pattern Recognition, July 23-25, 2009, Leipzig, Germany
785. Miriam Schmidt, Günther Palm, Friedhelm Schwenker, Spectral Graph Features for the Classification of Graphs and Graph Sequences, Computational Statistics, v.29 n.1-2, p.65-80, February 2014
786. Yukun Bao, Tao Xiong, Zhongyi Hu, Multi-step-ahead Time Series Prediction Using Multiple-output Support Vector Regression, Neurocomputing, 129, p.482-493, April, 2014
787. C. Orsenigo, C. Vercellis, Combining Discrete SVM and Fixed Cardinality Warping Distances for Multivariate Time Series Classification, Pattern Recognition, v.43 n.11, p.3787-3794, November, 2010
788. Bartosz Krawczyk, Michał Woźniak, Combining Diverse One-class Classifiers, Proceedings of the 7th International Conference on Hybrid Artificial Intelligent Systems, March 28-30, 2012, Salamanca, Spain
789. P. Pankajakshan, V. Kumar, Detail-preserving Image Information Restoration Guided by SVM based Noise Mapping, Digital Signal Processing, v.17 n.3, p.561-577, May, 2007
790. Fan Bu, Hang Li, Xiaoyan Zhu, String Re-writing Kernel, Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers, July 08-14, 2012, Jeju Island, Korea
791. Elham Parhizkar, Mahdi Abadi, BeeOWA, Neurocomputing, v.166 N.C, p.367-381, October 2015
792. Jia Cai, Yi Tang, Jianjun Wang, Kernel Canonical Correlation Analysis via Gradient Descent, Neurocomputing, v.182 N.C, p.322-331, March 2016
793. Yiming Ying, Colin Campbell, Mark Girolami, Analysis of SVM with Indefinite Kernels, Proceedings of the 22nd International Conference on Neural Information Processing Systems, p.2205-2213, December 07-10, 2009, Vancouver, British Columbia, Canada
794. Jongbin Ryu, Hyun S. Yang, Locality-preserving Descriptor for Robust Texture Feature Representation, Neurocomputing, v.214 N.C, p.729-738, November 2016
795. Ming-Feng Tsai, Chuan-Ju Wang, Po-Chuan Chien, Discovering Finance Keywords via Continuous-Space Language Models, ACM Transactions on Management Information Systems (TMIS), v.7 n.3, p.1-17, October 2016
796. Ahmed Kharrat, Karim Gasmi, Mohamed Ben Messaoud, Nacéra Benamrane, Mohamed Abid, Medical Image Classification Using An Optimal Feature Extraction Algorithm and a Supervised Classifier Technique, International Journal of Software Science and Computational Intelligence, v.3 n.2, p.19-33, April 2011
797. Shian-Chang Huang, Yu-Cheng Tang, Chih-Wei Lee, Ming-Jen Chang, Kernel Local Fisher Discriminant Analysis based Manifold-regularized SVM Model for Financial Distress Predictions, Expert Systems with Applications: An International Journal, v.39 n.3, p.3855-3861, February, 2012
798. Ouessai Asmaa, Keche Mokhtar, Ouamri Abdelaziz, Road Traffic Density Estimation Using Microscopic and Macroscopic Parameters, Image and Vision Computing, v.31 n.11, p.887-894, November, 2013
799. Yifei Li, Chaoli Wang, Ching-Kuang Shene, Extracting Flow Features via Supervised Streamline Segmentation, Computers and Graphics, v.52 N.C, p.79-92, November 2015
800. Sartra Wongthanavasu, Jetsada Ponkaew, A Cellular Automata-based Learning Method for Classification, Expert Systems with Applications: An International Journal, v.49 N.C, p.99-111, May 2016
801. Kurt Cutajar, Michael A. Osborne, John P. Cunningham, Maurizio Filippone, Preconditioning Kernel Matrices, Proceedings of the 33rd International Conference on International Conference on Machine Learning, June 19-24, 2016, New York, NY, USA
802. Muhammad Farooq, Ingo Steinwart, An SVM-like Approach for Expectile Regression, Computational Statistics & Data Analysis, v.109 N.C, p.159-181, May 2017
803. Hunny Mehrotra, Richa Singh, Mayank Vatsa, Banshidhar Majhi, Incremental Granular Relevance Vector Machine, Pattern Recognition, v.56 N.C, p.63-76, August 2016
804. Siyuan Liu, Shuhui Wang, Feida Zhu, Jinbo Zhang, Ramayya Krishnan, HYDRA: Large-scale Social Identity Linkage via Heterogeneous Behavior Modeling, Proceedings of the 2014 ACM SIGMOD International Conference on Management of Data, June 22-27, 2014, Snowbird, Utah, USA
805. Eyke Hüllermeier, Learning from Imprecise and Fuzzy Observations: Data Disambiguation through Generalized Loss Minimization, International Journal of Approximate Reasoning, v.55 n.7, p.1519-1534, October, 2014
806. Mario Frank, Fred A. Hamprecht, Image-based Supervision of a Periodically Working Machine, Pattern Analysis & Applications, v.16 n.3, p.407-416, August 2013
807. Wenye Li, Estimating Jaccard Index with Missing Observations: A Matrix Calibration Approach, Proceedings of the 28th International Conference on Neural Information Processing Systems, p.2620-2628, December 07-12, 2015, Montreal, Canada
808. Tianbao Yang, Mehrdad Mahdavi, Rong Jin, Lijun Zhang, Yang Zhou, Multiple Kernel Learning from Noisy Labels by Stochastic Programming, Proceedings of the 29th International Coference on International Conference on Machine Learning, p.123-130, June 26-July 01, 2012, Edinburgh, Scotland
809. Jesse Alama, Tom Heskes, Daniel Kühlwein, Evgeni Tsivtsivadze, Josef Urban, Premise Selection for Mathematics by Corpus Analysis and Kernel Methods, Journal of Automated Reasoning, v.52 n.2, p.191-213, February 2014
810. Yahya Forghani, Hadi Sadoghi Yazdi, Robust Support Vector Machine-trained Fuzzy System, Neural Networks, 50, p.154-165, February, 2014
811. Yeyong Pang, Shaojun Wang, Yu Peng, Xiyuan Peng, Nicholas J. Fraser, Philip H. W. Leong, A Microcoded Kernel Recursive Least Squares Processor Using FPGA Technology, ACM Transactions on Reconfigurable Technology and Systems (TRETS), v.10 n.1, p.1-22, December 2016
812. Ming-Der Yang, Tung-Ching Su, Automated Diagnosis of Sewer Pipe Defects based on Machine Learning Approaches, Expert Systems with Applications: An International Journal, v.35 n.3, p.1327-1337, October, 2008
813. Chin-Chun Chang, Tzung-Ying Lin, Linear Feature Extraction by Integrating Pairwise and Global Discriminatory Information via Sequential Forward Floating Selection and Kernel QR Factorization with Column Pivoting, Pattern Recognition, v.41 n.4, p.1373-1383, April, 2008
814. Jingneng Liu, Guihua Zeng, Jianping Fan, Fast Local Self-Similarity for Describing Interest Regions, Pattern Recognition Letters, v.33 n.9, p.1224-1235, July, 2012
815. Roland Kwitt, Nuno Vasconcelos, Nikhil Rasiwasia, Scene Recognition on the Semantic Manifold, Proceedings of the 12th European Conference on Computer Vision, October 07-13, 2012, Florence, Italy
816. Holger Franken, Alexander Seitz, Rainer Lehmann, Hans-Ulrich Häring, Norbert Stefan, Andreas Zell, Inferring Disease-related Metabolite Dependencies with a Bayesian Optimization Algorithm, Proceedings of the 10th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, April 11-13, 2012, Málaga, Spain
817. Changxin Gao, Nong Sang, Qiling Tang, On Selection and Combination of Weak Learners in AdaBoost, Pattern Recognition Letters, v.31 n.9, p.991-1001, July, 2010
818. Till Rumpf, Christoph Römer, Martin Weis, Markus Sökefeld, Roland Gerhards, Lutz Plümer, Sequential Support Vector Machine Classification for Small-grain Weed Species Discrimination with Special Regard to Cirsium Arvense and Galium Aparine, Computers and Electronics in Agriculture, 80, p.89-96, January, 2012
819. Turgay Celik, Tardi Tjahjadi, Multiscale Texture Classification Using Dual-tree Complex Wavelet Transform, Pattern Recognition Letters, v.30 n.3, p.331-339, February, 2009
820. M. Fatih Akay, Ipek Abasıkeleş, Predicting the Performance Measures of An Optical Distributed Shared Memory Multiprocessor by Using Support Vector Regression, Expert Systems with Applications: An International Journal, v.37 n.9, p.6293-6301, September, 2010
821. Xiaoyang Tan, Bill Triggs, Fusing Gabor and LBP Feature Sets for Kernel-based Face Recognition, Proceedings of the 3rd International Conference on Analysis and Modeling of Faces and Gestures, October 20, 2007, Rio De Janeiro, Brazil
822. Vladimir Norkin, Michiel Keyzer, On Stochastic Optimization and Statistical Learning in Reproducing Kernel Hilbert Spaces by Support Vector Machines (SVM), Informatica, v.20 n.2, p.273-292, April 2009
823. Jong Kyoung Kim, Sung-Yang Bang, Seungjin Choi, Sequence-driven Features for Prediction of Subcellular Localization of Proteins, Pattern Recognition, v.39 n.12, p.2301-2311, December, 2006
824. Estevão Esmi, Peter Sussner, Marcos Eduardo Valle, Fábio Sakuray, Laécio Barros, Fuzzy Associative Memories based on Subsethood and Similarity Measures with Applications to Speaker Identification, Proceedings of the 7th International Conference on Hybrid Artificial Intelligent Systems, March 28-30, 2012, Salamanca, Spain
825. Maria-Florina Balcan, Avrim Blum, Santosh Vempala, Kernels As Features: On Kernels, Margins, and Low-dimensional Mappings, Machine Learning, v.65 n.1, p.79-94, October 2006
826. Rong Jin, Steven C. H. Hoi, Tianbao Yang, Online Multiple Kernel Learning: Algorithms and Mistake Bounds, Proceedings of the 21st International Conference on Algorithmic Learning Theory, October 06-08, 2010, Canberra, Australia
827. GramSchmidt Process based Incremental Extreme Learning Machine, Neurocomputing, v.241 N.C, p.1-17, June 2017
828. Ashish Shrivastava, Jaishanker K. Pillai, Vishal M. Patel, Multiple Kernel-based Dictionary Learning for Weakly Supervised Classification, Pattern Recognition, v.48 n.8, p.2667-2675, August 2015
829. Chi-Yuan Yeh, Wen-Pin Su, Shie-Jue Lee, Employing Multiple-kernel Support Vector Machines for Counterfeit Banknote Recognition, Applied Soft Computing, v.11 n.1, p.1439-1447, January, 2011
830. Erik Zawadzki, Sebastien Lahaie, Nonparametric Scoring Rules, Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, p.3635-3641, January 25-30, 2015, Austin, Texas
831. Jacob R. Gardner, Matt J. Kusner, Zhixiang Xu, Kilian Q. Weinberger, John P. Cunningham, Bayesian Optimization with Inequality Constraints, Proceedings of the 31st International Conference on International Conference on Machine Learning, June 21-26, 2014, Beijing, China
832. Wen Chan, Jintao Du, Weidong Yang, Jinhui Tang, Xiangdong Zhou, Term Selection and Result Reranking for Question Retrieval by Exploiting Hierarchical Classification, Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management, November 03-07, 2014, Shanghai, China
833. Marco Cuturi, Jean-Philippe Vert, 2005 Special Issue: The Context-tree Kernel for Strings, Neural Networks, v.18 n.8, p.1111-1123, October 2005
834. Davide Anguita, Alessandro Ghio, Luca Oneto, Xavier Parra, Jorge Luis Reyes-Ortiz, Training Computationally Efficient SmartphoneBased Human Activity Recognition Models, Proceedings of the 23rd International Conference on Artificial Neural Networks and Machine Learning ICANN 2013, September 10-13, 2013
835. P. Mahesha, D. S. Vinod, Support Vector Machine-based Stuttering Dysfluency Classification Using GMM Supervectors, International Journal of Grid and Utility Computing, v.6 n.3/4, p.143-149, July 2015
836. Holger Wendland, Christian Rieger, Approximate Interpolation with Applications to Selecting Smoothing Parameters, Numerische Mathematik, v.101 n.4, p.729-748, October 2005
837. Daniel M. M. Da Costa, Henrique Passos, Sarajane Marques Peres, Clodoaldo A. M. De Lima, A Comparative Study of Feature Level Fusion Strategies for Multimodal Biometric Systems based on Face and Iris, Proceedings of the Annual Conference on Brazilian Symposium on Information Systems: Information Systems: A Computer Socio-Technical Perspective, May 26-29, 2015, Goiania, Goias, Brazil
838. Nicolas Couellan, Sophie Jan, Tom Jorquera, Jean-Pierre Georgé, Self-adaptive Support Vector Machine, Expert Systems with Applications: An International Journal, v.42 n.9, p.4284-4298, June 2015
839. Bin Gu, Victor S. Sheng, Zhijie Wang, Derek Ho, Said Osman, Shuo Li, Incremental Learning for Ν -Support Vector Regression, Neural Networks, v.67 N.C, p.140-150, July 2015
840. Ju-Jie Zhang, Min Fang, Hongchun Wang, Xiao Li, Dependence Maximization based Label Space Dimension Reduction for Multi-label Classification, Engineering Applications of Artificial Intelligence, v.45 N.C, p.453-463, October 2015
841. Amir F. Atiya, Ahmed Al-Ani, A Penalized Likelihood based Pattern Classification Algorithm, Pattern Recognition, v.42 n.11, p.2684-2694, November, 2009
842. Arash Afkanpour, András György, Csaba Szepesvári, Michael Bowling, A Randomized Mirror Descent Algorithm for Large Scale Multiple Kernel Learning, Proceedings of the 30th International Conference on International Conference on Machine Learning, June 16-21, 2013, Atlanta, GA, USA
843. Philipp Rapp, Martin Mesch, Harald Giessen, Cristina Tarín, Regression Methods for Ophthalmic Glucose Sensing Using Metamaterials, Journal of Electrical and Computer Engineering, 2011, p.5-5, January 2011
844. Truc-Vien T. Nguyen, Alessandro Moschitti, Giuseppe Riccardi, Kernel-based Reranking for Named-entity Extraction, Proceedings of the 23rd International Conference on Computational Linguistics: Posters, p.901-909, August 23-27, 2010, Beijing, China
845. Daniel Hernández-Lobato, Pablo Morales-Mombiela, David Lopez-Paz, Alberto Suárez, Non-linear Causal Inference Using Gaussianity Measures, The Journal of Machine Learning Research, v.17 n.1, p.939-977, January 2016
846. Lei Yang, Shaogao Lv, Junhui Wang, Model-free Variable Selection in Reproducing Kernel Hilbert Space, The Journal of Machine Learning Research, v.17 n.1, p.2885-2908, January 2016
847. Haizhang Zhang, Yuesheng Xu, Qinghui Zhang, Refinement of Operator-valued Reproducing Kernels, The Journal of Machine Learning Research, v.13 n.1, p.91-136, January 2012
848. Amar Khoukhi, Hybrid Soft Computing Systems for Reservoir PVT Properties Prediction, Computers & Geosciences, 44, p.109-119, July, 2012
849. Lev V. Utkin, Yulia A. Zhuk, Robust Novelty Detection in the Framework of a Contamination Neighbourhood, International Journal of Intelligent Information and Database Systems, v.7 n.3, p.205-224, May 2013
850. Lev V. Utkin, Yulia A. Zhuk, Robust Novelty Detection in the Framework of a Contamination Neighbourhood, International Journal of Intelligent Information and Database Systems, v.7 n.3, p.205-224, May 2013
851. Linus Hermansson, Tommi Kerola, Fredrik Johansson, Vinay Jethava, Devdatt Dubhashi, Entity Disambiguation in Anonymized Graphs Using Graph Kernels, Proceedings of the 22nd ACM International Conference on Conference on Information & Knowledge Management, October 27-November 01, 2013, San Francisco, California, USA
852. Gary Doran, Andrew Latham, Soumya Ray, A Unifying Framework for Learning Bag Labels from Generalized Multiple-instance Data, Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, p.1425-1431, July 09-15, 2016, New York, New York, USA
853. Takashi Takenouchi, Osamu Komori, Shinto Eguchi, An Extension of the Receiver Operating Characteristic Curve and Auc-optimal Classification, Neural Computation, v.24 n.10, p.2789-2824, October 2012
854. Lingfei Wu, Ian E.H. Yen, Jie Chen, Rui Yan, Revisiting Random Binning Features: Fast Convergence and Strong Parallelizability, Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, August 13-17, 2016, San Francisco, California, USA
855. Geraldo Braz Junior, Anselmo Cardoso De Paiva, Aristófanes Corrêa Silva, Alexandre Cesar Muniz De Oliveira, Classification of Breast Tissues Using Moran's Index and Geary's Coefficient As Texture Signatures and SVM, Computers in Biology and Medicine, v.39 n.12, p.1063-1072, December, 2009
856. John B. Halstead, Recruiter Selection Model and Implementation Within the United States Army, IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, v.39 n.1, p.93-100, January 2009
857. Huayan Wang, Qiang Yang, Transfer Learning by Structural Analogy, Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence, p.513-518, August 07-11, 2011, San Francisco, California
858. Martin Rasmussen, Janosch Rieger, Kevin N. Webster, Approximation of Reachable Sets Using Optimal Control and Support Vector Machines, Journal of Computational and Applied Mathematics, v.311 N.C, p.68-83, February 2017
859. Xingyu Wu, Xia Mao, Lijiang Chen, Yuli Xue, Alberto Rovetta, Point Context: An Effective Shape Descriptor for RST-Invariant Trajectory Recognition, Journal of Mathematical Imaging and Vision, v.56 n.3, p.441-454, November 2016
860. Tony Jebara, Risi Kondor, Andrew Howard, Probability Product Kernels, The Journal of Machine Learning Research, 5, p.819-844, 12/1/2004
861. Hastagiri P. Vanchinathan, Andreas Marfurt, Charles-Antoine Robelin, Donald Kossmann, Andreas Krause, Discovering Valuable Items from Massive Data, Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, August 10-13, 2015, Sydney, NSW, Australia
862. Wenting Lu, Lei Li, Jingxuan Li, Tao Li, Honggang Zhang, Jun Guo, A Multimedia Information Fusion Framework for Web Image Categorization, Multimedia Tools and Applications, v.70 n.3, p.1453-1486, June 2014
863. Simon Barthelmé, Nicolas Chopin, The Poisson Transform for Unnormalised Statistical Models, Statistics and Computing, v.25 n.4, p.767-780, July 2015
864. Xin Yuan, Ricardo Henao, Ephraim L. Tsalik, Raymond J. Langley, Lawrence Carin, Non-Gaussian Discriminative Factor Models via the Max-margin Rank-likelihood, Proceedings of the 32nd International Conference on International Conference on Machine Learning, July 06-11, 2015, Lille, France
865. David Lopez-Paz, Suvrit Sra, Alexander J. Smola, Zoubin Ghahramani, Bernhard Schölkopf, Randomized Nonlinear Component Analysis, Proceedings of the 31st International Conference on International Conference on Machine Learning, June 21-26, 2014, Beijing, China
866. Xiang-Yang Wang, Qin-Yan Wang, Hong-Ying Yang, Juan Bu, Color Image Segmentation Using Automatic Pixel Classification with Support Vector Machine, Neurocomputing, v.74 n.18, p.3898-3911, November, 2011
867. Shusen Wang, Zhihua Zhang, Tong Zhang, Towards More Efficient SPSD Matrix Approximation and CUR Matrix Decomposition, The Journal of Machine Learning Research, v.17 n.1, p.7329-7377, January 2016
868. Lubor Ladicky, Chris Russell, Pushmeet Kohli, Philip H. S. Torr, Graph Cut based Inference with Co-occurrence Statistics, Proceedings of the 11th European Conference on Computer Vision: Part V, September 05-11, 2010, Heraklion, Crete, Greece
869. Eduard Gabriel Băzăvan, Fuxin Li, Cristian Sminchisescu, Fourier Kernel Learning, Proceedings of the 12th European Conference on Computer Vision, October 07-13, 2012, Florence, Italy
870. Kuo-Ching Ying, Shih-Wei Lin, Zne-Jung Lee, Yen-Tim Lin, An Ensemble Approach Applied to Classify Spam E-mails, Expert Systems with Applications: An International Journal, v.37 n.3, p.2197-2201, March, 2010
871. Chong Zhang, Chongxun Zheng, Xiaolin Yu, Yi Ouyang, Estimating VDT Mental Fatigue Using Multichannel Linear Descriptors and KPCA-HMM, EURASIP Journal on Advances in Signal Processing, 2008, p.1-11, January 2008
872. Yusuke Torii, Shigeo Abe, Decomposition Techniques for Training Linear Programming Support Vector Machines, Neurocomputing, v.72 n.4-6, p.973-984, January, 2009
873. Kar-Ann Toh, Youngsung Kim, Sangyoun Lee, Jaihie Kim, Fusion of Visual and Infra-red Face Scores by Weighted Power Series, Pattern Recognition Letters, v.29 n.5, p.603-615, April, 2008
874. Pengfei Zhu, Qinghua Hu, Rule Extraction from Support Vector Machines based on Consistent Region Covering Reduction, Knowledge-Based Systems, 42, p.1-8, April, 2013
875. Shan-Hung Wu, Keng-Pei Lin, Chung-Min Chen, Ming-Syan Chen, Asymmetric Support Vector Machines: Low False-positive Learning under the User Tolerance, Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, August 24-27, 2008, Las Vegas, Nevada, USA
876. Fernando Soares Sérvulo De Oliveira, Antonio Oseas De Carvalho Filho, Aristófanes Corrêa Silva, Anselmo Cardoso De Paiva, Marcelo Gattass, Classification of Breast Regions As Mass and Non-mass based on Digital Mammograms Using Taxonomic Indexes and SVM, Computers in Biology and Medicine, v.57 N.C, p.42-53, February 2015
877. Shuyuan Yang, Min Wang, Li Jin, Shigang Wang, Fang Liu, Licheng Jiao, Learning Compressive Sampling via Multiscale and Steerable Support Value Transform, Knowledge-Based Systems, v.82 N.C, p.128-138, July 2015
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879. Ting Liu, Xiao Ding, Yiheng Chen, Haochen Chen, Maosheng Guo, Predicting Movie Box-office Revenues by Exploiting Large-scale Social Media Content, Multimedia Tools and Applications, v.75 n.3, p.1509-1528, February 2016
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881. Ang Li, Zhenjiang Miao, Yigang Cen, Tian Wang, Viacheslav Voronin, Histogram of Maximal Optical Flow Projection for Abnormal Events Detection in Crowded Scenes, International Journal of Distributed Sensor Networks, 2015, p.3-3, January 2015
882. Matthias Feurer, Jost Tobias Springenberg, Frank Hutter, Using Meta-learning to Initialize Bayesian Optimization of Hyperparameters, Proceedings of the 2014 International Conference on Meta-learning and Algorithm Selection, September 19, 2014, Prague, Czech Republic
883. Hachem Kadri, Alain Rakotomamonjy, Francis Bach, Philippe Preux, Multiple Operator-valued Kernel Learning, Proceedings of the 25th International Conference on Neural Information Processing Systems, p.2429-2437, December 03-06, 2012, Lake Tahoe, Nevada
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888. Dacheng Tao, Xuelong Li, Xindong Wu, Weiming Hu, Stephen J. Maybank, Supervised Tensor Learning, Knowledge and Information Systems, v.13 n.1, p.1-42, September 2007
889. Koby Crammer, Ofer Dekel, Joseph Keshet, Shai Shalev-Shwartz, Yoram Singer, Online Passive-Aggressive Algorithms, The Journal of Machine Learning Research, 7, p.551-585, 12/1/2006
890. Vladimir I. Norkin, Michiel A. Keyzer, On Convergence of Kernel Learning Estimators, SIAM Journal on Optimization, v.20 n.3, p.1205-1223, August 2009
891. Yutaka I. Leon-Suematsu, Kentaro Inui, Sadao Kurohashi, Yutaka Kidawara, Web Spam Detection by Exploring Densely Connected Subgraphs, Proceedings of the 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology, p.124-129, August 22-27, 2011
892. Takumi Kobayashi, Kernel-based Transition Probability Toward Similarity Measure for Semi-supervised Learning, Pattern Recognition, v.47 n.5, p.1994-2010, May, 2014
893. Gabriel Gómez Sena, Pablo Belzarena, Statistical Traffic Classification by Boosting Support Vector Machines, Proceedings of the 7th Latin American Networking Conference, October 04-05, 2012, Medellín, Columbia
894. Santiago D. Villalba, Pádraig Cunningham, An Evaluation of Dimension Reduction Techniques for One-class Classification, Artificial Intelligence Review, v.27 n.4, p.273-294, April 2007
895. Yuichi Takano, Jun-Ya Gotoh, Multi-period Portfolio Selection Using Kernel-based Control Policy with Dimensionality Reduction, Expert Systems with Applications: An International Journal, v.41 n.8, p.3901-3914, June, 2014
896. Ying Zhao, Justin Zobel, Searching with Style: Authorship Attribution in Classic Literature, Proceedings of the Thirtieth Australasian Conference on Computer Science, p.59-68, January 30-February 02, 2007, Ballarat, Victoria, Australia
897. Palle Jorgensen, Feng Tian, Discrete Reproducing Kernel Hilbert Spaces: Sampling and Distribution of Dirac-masses, The Journal of Machine Learning Research, v.16 n.1, p.3079-3114, January 2015
898. Buhwan Jeong, Daewon Lee, Jaewook Lee, Hyunbo Cho, Support for Seamless Data Exchanges Between Web Services through Information Mapping Analysis Using Kernel Methods, Expert Systems with Applications: An International Journal, v.36 n.1, p.358-365, January, 2009
899. Truc-Vien T. Nguyen, Alessandro Moschitti, Giuseppe Riccardi, Convolution Kernels on Constituent, Dependency and Sequential Structures for Relation Extraction, Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 3, August 06-07, 2009, Singapore
900. Franz Pernkopf, Michael Wohlmayr, Stochastic Margin-based Structure Learning of Bayesian Network Classifiers, Pattern Recognition, v.46 n.2, p.464-471, February, 2013
901. Riwal Lefort, Ludovico Fusco, Olivier Pertz, François Fleuret, Machine Learning-based Tools to Model and to Remove the Off-target Effect, Pattern Analysis & Applications, v.20 n.1, p.87-100, February 2017
902. Gao Huang, Tianchi Liu, Yan Yang, Zhiping Lin, Shiji Song, Cheng Wu, Discriminative Clustering via Extreme Learning Machine, Neural Networks, v.70 N.C, p.1-8, October 2015
903. Giorgio Patrini, Frank Nielsen, Richard Nock, Marcello Carioni, Loss Factorization, Weakly Supervised Learning and Label Noise Robustness, Proceedings of the 33rd International Conference on International Conference on Machine Learning, June 19-24, 2016, New York, NY, USA
904. Kirthevasan Kandasamy, Yaoliang Yu, Additive Approximations in High Dimensional Nonparametric Regression via the SALSA, Proceedings of the 33rd International Conference on International Conference on Machine Learning, June 19-24, 2016, New York, NY, USA
905. Stergios Papadimitriou, Konstantinos Terzidis, Growing Kernel-based Self-organized Maps Trained with Supervised Bias, Intelligent Data Analysis, v.8 n.2, p.111-130, April 2004
906. Oliver Kramer, Unsupervised Nearest Neighbor Regression for Dimensionality Reduction, Soft Computing - A Fusion of Foundations, Methodologies and Applications, v.19 n.6, p.1647-1661, June 2015
907. Tristan Mary-Huard, Stéphane Robin, Jean-Jacques Daudin, A Penalized Criterion for Variable Selection in Classification, Journal of Multivariate Analysis, v.98 n.4, p.695-705, April, 2007
908. Jie Chen, Kian Hsiang Low, Colin Keng-Yan Tan, Ali Oran, Patrick Jaillet, John Dolan, Gaurav Sukhatme, Decentralized Data Fusion and Active Sensing with Mobile Sensors for Modeling and Predicting Spatiotemporal Traffic Phenomena, Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, August 14-18, 2012, Catalina Island, CA
909. Feiping Nie, Shiming Xiang, Yangqing Jia, Changshui Zhang, Semi-supervised Orthogonal Discriminant Analysis via Label Propagation, Pattern Recognition, v.42 n.11, p.2615-2627, November, 2009
910. Longhua Qian, Guodong Zhou, Qiaoming Zhu, Employing Constituent Dependency Information for Tree Kernel-Based Semantic Relation Extraction Between Named Entities, ACM Transactions on Asian Language Information Processing (TALIP), v.10 n.3, p.1-24, September 2011
911. D. Sculley, Robert G. Malkin, Sugato Basu, Roberto J. Bayardo, Predicting Bounce Rates in Sponsored Search Advertisements, Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, June 28-July 01, 2009, Paris, France
912. Gang Wang, Zhicheng Wang, Yufei Chen, Xianhui Liu, Yingchun Ren, Lei Peng, Learning Coherent Vector Fields for Robust Point Matching under Manifold Regularization, Neurocomputing, v.216 N.C, p.393-401, December 2016
913. Tonatiuh Peña Centeno, Neil D. Lawrence, Optimising Kernel Parameters and Regularisation Coefficients for Non-linear Discriminant Analysis, The Journal of Machine Learning Research, 7, p.455-491, 12/1/2006
914. Haizhang Zhang, Yuesheng Xu, Jun Zhang, Reproducing Kernel Banach Spaces for Machine Learning, The Journal of Machine Learning Research, 10, p.2741-2775, 12/1/2009
915. H. -S. Park, Y. -D. Chung, S. -K. Oh, W. Pedrycz, H. -K. Kim, Design of Information Granule-oriented RBF Neural Networks and Its Application to Power Supply for High-field Magnet, Engineering Applications of Artificial Intelligence, v.24 n.3, p.543-554, April, 2011
916. Giorgio Gnecco, Marcello Sanguineti, Accuracy of Suboptimal Solutions to Kernel Principal Component Analysis, Computational Optimization and Applications, v.42 n.2, p.265-287, March 2009
917. Lu Bai, Edwin R. Hancock, Graph Kernels from the Jensen-Shannon Divergence, Journal of Mathematical Imaging and Vision, v.47 n.1-2, p.60-69, September 2013
918. Haizhang Zhang, Jun Zhang, Regularized Learning in Banach Spaces As An Optimization Problem: Representer Theorems, Journal of Global Optimization, v.54 n.2, p.235-250, October 2012
919. Tobias Petri, Robert Küffner, Ralf Zimmer, Experiment Specific Expression Patterns, Proceedings of the 15th Annual International Conference on Research in Computational Molecular Biology, p.339-354, March 28-31, 2011, Vancouver, BC, Canada
920. Francesca Bovolo, Lorenzo Bruzzone, Lorenzo Carlin, A Novel Technique for Subpixel Image Classification based on Support Vector Machine, IEEE Transactions on Image Processing, v.19 n.11, p.2983-2999, November 2010
921. Haizhang Zhang, Jun Zhang, Vector-valued Reproducing Kernel Banach Spaces with Applications to Multi-task Learning, Journal of Complexity, v.29 n.2, p.195-215, April, 2013
922. Ye Tian, Jian Luo, A New Branch-and-bound Approach to Semi-supervised Support Vector Machine, Soft Computing - A Fusion of Foundations, Methodologies and Applications, v.21 n.1, p.245-254, January 2017
923. Michel Ballings, Dirk Van Den Poel, Kernel Factory: An Ensemble of Kernel Machines, Expert Systems with Applications: An International Journal, v.40 n.8, p.2904-2913, June, 2013
924. Godwin Caruana, Maozhen Li, Yang Liu, An Ontology Enhanced Parallel SVM for Scalable Spam Filter Training, Neurocomputing, 108, p.45-57, May, 2013
925. S. Monira Sumi, M. Faisal Zaman, Hideo Hirose, A Rainfall Forecasting Method Using Machine Learning Models and Its Application to the Fukuoka City Case, International Journal of Applied Mathematics and Computer Science, v.22 n.4, p.841-854, 12 2012
926. Mehdi Boroumand, Jessica Fridrich, Boosting Steganalysis with Explicit Feature Maps, Proceedings of the 4th ACM Workshop on Information Hiding and Multimedia Security, June 20-22, 2016, Vigo, Galicia, Spain
927. Yinan Yu, Tomas McKelvey, A Robust Subspace Classification Scheme based on Empirical Intersection Removal and Sparse Approximation, Integrated Computer-Aided Engineering, v.22 n.1, p.59-69, January 2015
928. Olfa Ben Ahmed, Jenny Benois-Pineau, Michèle Allard, Chokri Ben Amar, Gwénaëlle Catheline, Classification of Alzheimer's Disease Subjects from MRI Using Hippocampal Visual Features, Multimedia Tools and Applications, v.74 n.4, p.1249-1266, February 2015
929. Milica Gasic, Steve Young, Gaussian Processes for POMDP-Based Dialogue Manager Optimization, IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP), v.22 n.1, p.28-40, January 2014
930. Pedro A. Forero, Alfonso Cano, Georgios B. Giannakis, Consensus-Based Distributed Support Vector Machines, The Journal of Machine Learning Research, 11, p.1663-1707, 3/1/2010
931. James Abello, Peter Broadwell, Timothy R. Tangherlini, Computational Folkloristics, Communications of the ACM, v.55 n.7, July 2012
932. Jan Peters, Stefan Schaal, Learning to Control in Operational Space, International Journal of Robotics Research, v.27 n.2, p.197-212, February 2008
933. Melih Kandemir, Akos Vetek, Mehmet Gönen, Arto Klami, Samuel Kaski, Multi-task and Multi-view Learning of User State, Neurocomputing, 139, p.97-106, September, 2014
934. Chi-Yuan Yeh, Wen-Pin Su, Shie-Jue Lee, An Efficient Multiple-kernel Learning for Pattern Classification, Expert Systems with Applications: An International Journal, v.40 n.9, p.3491-3499, July, 2013
935. Hanchao Qi, Armeen Taeb, Shannon M. Hughes, Visual Stylometry Using Background Selection and Wavelet-HMT-based Fisher Information Distances for Attribution and Dating of Impressionist Paintings, Signal Processing, v.93 n.3, p.541-553, March, 2013
936. Mehmet GöNen, Ethem AlpaydıN, Localized Algorithms for Multiple Kernel Learning, Pattern Recognition, v.46 n.3, p.795-807, March, 2013
937. Dandan Li, Chung-Ping Kwong, Dik Lun Lee, Unified Linear Subspace Approach to Semantic Analysis, Journal of the American Society for Information Science and Technology, v.61 n.1, p.175-189, January 2010
938. Takashi Takenouchi, Shin Ishii, A Multiclass Classification Method based on Decoding of Binary Classifiers, Neural Computation, v.21 n.7, p.2049-2081, July 2009
939. Sebastian Schneckener, Linus Görlitz, Heidrun Ellinger-Ziegelbauer, Hans-Jürgen Ahr, Andreas Schuppert, Research Article: An Elastic Network Model to Identify Characteristic Stress Response Genes, Computational Biology and Chemistry, v.34 n.3, p.193-202, June, 2010
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941. Menglong Yang, Yiguang Liu, Baojiang Zhong, Zheng Li, Classification by Nearness in Complementary Subspaces, Pattern Analysis & Applications, v.16 n.4, p.609-622, November 2013
942. Andreas Christmann, Robert Hable, Consistency of Support Vector Machines Using Additive Kernels for Additive Models, Computational Statistics & Data Analysis, v.56 n.4, p.854-873, April, 2012
943. Davide Boscaini, Umberto Castellani, A Sparse Coding Approach for Local-to-global 3D Shape Description, The Visual Computer: International Journal of Computer Graphics, v.30 n.11, p.1233-1245, November 2014
944. Oliver Kramer, Fabian Gieseke, Evolutionary Kernel Density Regression, Expert Systems with Applications: An International Journal, v.39 n.10, p.9246-9254, August, 2012
945. Guo-Cyuan Chen, Chia-Feng Juang, An Accuracy-oriented Self-splitting Fuzzy Classifier with Support Vector Learning in High-order Expanded Consequent Space, Applied Soft Computing, 15, p.231-242, February, 2014
946. Manuel Herrera, Aurore Guglielmetti, Manyu Xiao, Rajan Filomeno Coelho, Metamodel-assisted Optimization based on Multiple Kernel Regression for Mixed Variables, Structural and Multidisciplinary Optimization, v.49 n.6, p.979-991, June 2014
947. Grégoire Montavon, Mikio L. Braun, Klaus-Robert Müller, Kernel Analysis of Deep Networks, The Journal of Machine Learning Research, 12, p.2563-2581, 2/1/2011
948. Bertrand Fontaine, Herbert Peremans, Bat Echolocation Processing Using First-spike Latency Coding, Neural Networks, v.22 n.10, p.1372-1382, December, 2009
949. Kilian Q. Weinberger, Lawrence K. Saul, Unsupervised Learning of Image Manifolds by Semidefinite Programming, International Journal of Computer Vision, v.70 n.1, p.77-90, October 2006
950. Wolfgang Heidl, Stefan Thumfart, Edwin Lughofer, Christian Eitzinger, Erich Peter Klement, Machine Learning based Analysis of Gender Differences in Visual Inspection Decision Making, Information Sciences: An International Journal, 224, p.62-76, March, 2013
951. L'ubor Ladický, Chris Russell, Pushmeet Kohli, Philip H. Torr, Inference Methods for CRFs with Co-occurrence Statistics, International Journal of Computer Vision, v.103 n.2, p.213-225, June 2013
952. Jyrko Correa-Morris, Dustin L. Espinosa-Isidrón, Denis R. Álvarez-Nadiozhin, An Incremental Nested Partition Method for Data Clustering, Pattern Recognition, v.43 n.7, p.2439-2455, July, 2010
953. Peng Zhao, Bin Yu, Stagewise Lasso, The Journal of Machine Learning Research, 8, p.2701-2726, 12/1/2007
954. Gianluigi Pillonetto, Consistent Identification of Wiener Systems: A Machine Learning Viewpoint, Automatica (Journal of IFAC), v.49 n.9, p.2704-2712, September, 2013
955. Rita Chattopadhyay, Qian Sun, Wei Fan, Ian Davidson, Sethuraman Panchanathan, Jieping Ye, Multisource Domain Adaptation and Its Application to Early Detection of Fatigue, ACM Transactions on Knowledge Discovery from Data (TKDD), v.6 n.4, p.1-26, December 2012
956. Chia-Hui Huang, A Reduced Support Vector Machine Approach for Interval Regression Analysis, Information Sciences: An International Journal, 217, p.56-64, December, 2012
957. Ashwinkumar Badanidiyuru, Baharan Mirzasoleiman, Amin Karbasi, Andreas Krause, Streaming Submodular Maximization: Massive Data Summarization on the Fly, Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, August 24-27, 2014, New York, New York, USA
958. Emanuele Frandi, Ricardo Ñanculef, Stefano Lodi, Claudio Sartori, Johan A. Suykens, Fast and Scalable Lasso via Stochastic Frank---Wolfe Methods with a Convergence Guarantee, Machine Learning, v.104 n.2-3, p.195-221, September 2016
959. Chih-Chia Yao, Pao-Ta Yu, The Optimal Design of Weighted Order Statistics Filters by Using Support Vector Machines, EURASIP Journal on Applied Signal Processing, 2006, p.6-6, 01 January
960. Rafael M. O. Cruz, George D. C. Cavalcanti, Ing Ren Tsang, Robert Sabourin, Feature Representation Selection based on Classifier Projection Space and Oracle Analysis, Expert Systems with Applications: An International Journal, v.40 n.9, p.3813-3827, July, 2013
961. Fredrik D. Johansson, Devdatt Dubhashi, Learning with Similarity Functions on Graphs Using Matchings of Geometric Embeddings, Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, August 10-13, 2015, Sydney, NSW, Australia
962. Khuong An Nguyen, Zhiyuan Luo, Reliable Indoor Location Prediction Using Conformal Prediction, Annals of Mathematics and Artificial Intelligence, v.74 n.1-2, p.133-153, June 2015
963. Aftab Khan, James Nicholson, Sebastian Mellor, Daniel Jackson, Karim Ladha, Cassim Ladha, Jon Hand, Joseph Clarke, Patrick Olivier, Thomas Plötz, Occupancy Monitoring Using Environmental & Context Sensors and a Hierarchical Analysis Framework, Proceedings of the 1st ACM Conference on Embedded Systems for Energy-Efficient Buildings, November 03-06, 2014, Memphis, Tennessee
964. Rami N. Khushaba, Sarath Kodagoda, Sara Lal, Gamini Dissanayake, Uncorrelated Fuzzy Neighborhood Preserving Analysis based Feature Projection for Driver Drowsiness Recognition, Fuzzy Sets and Systems, 221, p.90-111, June, 2013
965. Gavin C. Cawley, Nicola L. C. Talbot, The Evidence Framework Applied to Sparse Kernel Logistic Regression, Neurocomputing, 64, p.119-135, March, 2005
966. Jalal Shiri, Ozgur Kisi, Heesung Yoon, Kang-Kun Lee, Amir Hossein Nazemi, Predicting Groundwater Level Fluctuations with Meteorological Effect Implications-A Comparative Study Among Soft Computing Techniques, Computers & Geosciences, v.56 N.C, p.32-44, July 2013
967. Marko Heikkilä, Matti Pietikäinen, Cordelia Schmid, Description of Interest Regions with Local Binary Patterns, Pattern Recognition, v.42 n.3, p.425-436, March, 2009
968. Tansu Alpcan, A Framework for Optimization under Limited Information, Journal of Global Optimization, v.55 n.3, p.681-706, March 2013
969. Anindya Halder, Ashish Ghosh, Susmita Ghosh, Aggregation Pheromone Density Based Pattern Classification, Fundamenta Informaticae, v.92 n.4, p.345-362, June 2009
970. Anindya Halder, Ashish Ghosh, Susmita Ghosh, Aggregation Pheromone Density Based Pattern Classification, Fundamenta Informaticae, v.92 n.4, p.345-362, December 2009
971. D. Gorisse, M. Cord, F. Precioso, SALSAS: Sub-linear Active Learning Strategy with Approximate K-NN Search, Pattern Recognition, v.44 n.10-11, p.2343-2357, October, 2011
972. Masahiro Fujita, Intelligence Dynamics: A Concept and Preliminary Experiments for Open-ended Learning Agents, Autonomous Agents and Multi-Agent Systems, v.19 n.3, p.248-271, December 2009
973. Sheng Chen, Xia Hong, Bing L. Luk, Chris J. Harris, Non-linear System Identification Using Particle Swarm Optimisation Tuned Radial Basis Function Models, International Journal of Bio-Inspired Computation, v.1 n.4, p.246-258, April 2009
974. Horng-Horng Lin, Tyng-Luh Liu, Jen-Hui Chuang, Learning a Scene Background Model via Classification, IEEE Transactions on Signal Processing, v.57 n.5, p.1641-1654, May 2009
975. Ping Zhu, Yu Zhang, Guanlong Chen, Metamodeling Development for Reliability-based Design Optimization of Automotive Body Structure, Computers in Industry, v.62 n.7, p.729-741, September, 2011
976. Yan Tian, Leonid Sigal, Fernando De La Torre, Yonghua Jia, Editor's Choice Article: Canonical Locality Preserving Latent Variable Model for Discriminative Pose Inference, Image and Vision Computing, v.31 n.3, p.223-230, March, 2013
977. Kush R. Varshney, Alan S. Willsky, Classification Using Geometric Level Sets, The Journal of Machine Learning Research, 11, p.491-516, 3/1/2010
978. Mehmet Gönen, Adam A. Margolin, Kernelized Bayesian Transfer Learning, Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, p.1831-1839, July 27-31, 2014, Québec City, Québec, Canada
979. Bac Nguyen, Carlos Morell, Bernard De Baets, Supervised Distance Metric Learning through Maximization of the Jeffrey Divergence, Pattern Recognition, v.64 N.C, p.215-225, April 2017
980. Yunlong Feng, Shao-Gao Lv, Hanyuan Hang, Johan A. K. Suykens, Kernelized Elastic Net Regularization: Generalization Bounds, and Sparse Recovery, Neural Computation, v.28 n.3, p.525-562, March 2016
981. Danilo DonGiovanni, Lucia Maria Vaina, Select and Cluster, Computational Intelligence and Neuroscience, 2016, p.10, August 2016
982. Manu Nandan, Pramod P. Khargonekar, Sachin S. Talathi, Fast SVM Training Using Approximate Extreme Points, The Journal of Machine Learning Research, v.15 n.1, p.59-98, January 2014
983. Tao Xiong, Yukun Bao, Zhongyi Hu, Multiple-output Support Vector Regression with a Firefly Algorithm for Interval-valued Stock Price Index Forecasting, Knowledge-Based Systems, 55, p.87-100, January, 2014
984. Matt J. Kusner, Jacob R. Gardner, Roman Garnett, Kilian Q. Weinberger, Differentially Private Bayesian Optimization, Proceedings of the 32nd International Conference on International Conference on Machine Learning, July 06-11, 2015, Lille, France
985. Yongchang Ma, Mashrur Chowdhury, Adel Sadek, Mansoureh Jeihani, Real-time Highway Traffic Condition Assessment Framework Using Vehicle-infrastructure Integration (VII) with Artificial Intelligence (AI), IEEE Transactions on Intelligent Transportation Systems, v.10 n.4, p.615-627, December 2009
986. Mohammad Taha Bahadori, David Kale, Yingying Fan, Yan Liu, Functional Subspace Clustering with Application to Time Series, Proceedings of the 32nd International Conference on International Conference on Machine Learning, July 06-11, 2015, Lille, France
987. Behnam Vahdani, Farzad Razavi, S. Meysam Mousavi, A High Performing Meta-heuristic for Training Support Vector Regression in Performance Forecasting of Supply Chain, Neural Computing and Applications, v.27 n.8, p.2441-2451, November 2016
988. Xue-wen Chen, Byron Gerlach, Dechang Chen, Zhenqiu Liu, Structural Risk Minimisation based Gene Expression Profiling Analysis, International Journal of Bioinformatics Research and Applications, v.3 n.2, p.153-169, May 2007
989. J. L. Castro, L. D. Flores-Hidalgo, C. J. Mantas, J. M. Puche, Extraction of Fuzzy Rules from Support Vector Machines, Fuzzy Sets and Systems, v.158 n.18, p.2057-2077, September, 2007
990. Ahmed Kharrat, Mohamed Abid, Toward Efficient Segmentation of Brain Tumors Based on Support Vector Machine Classifier Through Optimized RBF Kernel Parameters and Optimal Texture Features, International Journal of Cognitive Informatics and Natural Intelligence, v.8 n.2, p.15-33, April 2014
991. Yongqiao Wang, Modeling Financial Dependence with Support Vector Regression, Intelligent Data Analysis, v.17 n.2, p.233-249, March 2013
992. Fabian Gieseke, Antti Airola, Tapio Pahikkala, Oliver Kramer, Fast and Simple Gradient-based Optimization for Semi-supervised Support Vector Machines, Neurocomputing, 123, p.23-32, January, 2014
993. Andreas Christmann, Ingo Steinwart, On Robustness Properties of Convex Risk Minimization Methods for Pattern Recognition, The Journal of Machine Learning Research, 5, p.1007-1034, 12/1/2004
994. Guibo Zhu, Jinqiao Wang, Yi Wu, Xiaoyu Zhang, Hanqing Lu, MC-HOG Correlation Tracking with Saliency Proposal, Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, February 12-17, 2016, Phoenix, Arizona
995. Gaofeng Jia, Alexandros A. Taflanidis, James L. Beck, Non-parametric Stochastic Subset Optimization for Design Problems with Reliability Constraints, Structural and Multidisciplinary Optimization, v.52 n.6, p.1185-1204, December 2015
996. Thomas Desautels, Andreas Krause, Joel W. Burdick, Parallelizing Exploration-exploitation Tradeoffs in Gaussian Process Bandit Optimization, The Journal of Machine Learning Research, v.15 n.1, p.3873-3923, January 2014
997. Zhixiang Xu, Matt J. Kusner, Kilian Q. Weinberger, Minmin Chen, Olivier Chapelle, Classifier Cascades and Trees for Minimizing Feature Evaluation Cost, The Journal of Machine Learning Research, v.15 n.1, p.2113-2144, January 2014
998. Dewang Chen, Lijuan Wang, Lingxi Li, Position Computation Models for High-speed Train based on Support Vector Machine Approach, Applied Soft Computing, v.30 N.C, p.758-766, May 2015
999. Keng-Pei Lin, Yi-Wei Chang, Ming-Syan Chen, Secure Support Vector Machines Outsourcing with Random Linear Transformation, Knowledge and Information Systems, v.44 n.1, p.147-176, July 2015
1000. Chao-Ton Su, Chien-Hsin Yang, Feature Selection for the SVM: An Application to Hypertension Diagnosis, Expert Systems with Applications: An International Journal, v.34 n.1, p.754-763, January, 2008
1001. Gerben Klaas Dirk De Vries, Maarten Van Someren, An Analysis of Alignment and Integral based Kernels for Machine Learning from Vessel Trajectories, Expert Systems with Applications: An International Journal, v.41 n.16, p.7596-7607, November, 2014
1002. Tony Jebara, Multitask Sparsity via Maximum Entropy Discrimination, The Journal of Machine Learning Research, 12, p.75-110, 2/1/2011
1003. Hyeongjin Song, K. K. Choi, Ikjin Lee, Liang Zhao, David Lamb, Adaptive Virtual Support Vector Machine for Reliability Analysis of High-dimensional Problems, Structural and Multidisciplinary Optimization, v.47 n.4, p.479-491, April 2013
1004. Huseyin Ince, Theodore B. Trafalis, A Hybrid Model for Exchange Rate Prediction, Decision Support Systems, v.42 n.2, p.1054-1062, November 2006
1005. Alexander Binder, Klaus-Robert Müller, Motoaki Kawanabe, On Taxonomies for Multi-class Image Categorization, International Journal of Computer Vision, v.99 n.3, p.281-301, September 2012
1006. Olivier Pietquin, Matthieu Geist, Senthilkumar Chandramohan, Hervé Frezza-Buet, Sample-efficient Batch Reinforcement Learning for Dialogue Management Optimization, ACM Transactions on Speech and Language Processing (TSLP), v.7 n.3, p.1-21, May 2011
1007. A. F. Al-Anazi, I. D. Gates, Support Vector Regression for Porosity Prediction in a Heterogeneous Reservoir: A Comparative Study, Computers & Geosciences, v.36 n.12, p.1494-1503, December, 2010
1008. V. Ceperic, G. Gielen, A. Baric, Sparse Multikernel Support Vector Regression Machines Trained by Active Learning, Expert Systems with Applications: An International Journal, v.39 n.12, p.11029-11035, September, 2012
1009. Adrian Ulges, Christian Schulze, Markus Koch, Thomas M. Breuel, Learning Automatic Concept Detectors from Online Video, Computer Vision and Image Understanding, v.114 n.4, p.429-438, April, 2010
1010. Germán Capdehourat, Andrés Corez, Anabella Bazzano, Rodrigo Alonso, Pablo Musé, Toward a Combined Tool to Assist Dermatologists in Melanoma Detection from Dermoscopic Images of Pigmented Skin Lesions, Pattern Recognition Letters, v.32 n.16, p.2187-2196, December, 2011
1011. C. -S. Lee, A. Elgammal, Coupled Visual and Kinematic Manifold Models for Tracking, International Journal of Computer Vision, v.87 n.1-2, p.118-139, March 2010
1012. Mathieu Fauvel, Jocelyn Chanussot, Jón Atli Benediktsson, Kernel Principal Component Analysis for the Classification of Hyperspectral Remote Sensing Data over Urban Areas, EURASIP Journal on Advances in Signal Processing, 2009, p.1-14, January 2009
1013. Aftab Khan, Sebastian Mellor, Eugen Berlin, Robin Thompson, Roisin McNaney, Patrick Olivier, Thomas Plötz, Beyond Activity Recognition: Skill Assessment from Accelerometer Data, Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing, September 07-11, 2015, Osaka, Japan
1014. Lin Li, Austin J. Brockmeier, John S. Choi, Joseph T. Francis, Justin C. Sanchez, José C. Príncipe, A Tensor-product-kernel Framework for Multiscale Neural Activity Decoding and Control, Computational Intelligence and Neuroscience, 2014, p.2-2, January 2014
1015. Fei Wang, Jimeng Sun, Survey on Distance Metric Learning and Dimensionality Reduction in Data Mining, Data Mining and Knowledge Discovery, v.29 n.2, p.534-564, March 2015
1016. Wei Tong, Yi Yang, Lu Jiang, Shoou-I Yu, Zhenzhong Lan, Zhigang Ma, Waito Sze, Ehsan Younessian, Alexander G. Hauptmann, E-LAMP: Integration of Innovative Ideas for Multimedia Event Detection, Machine Vision and Applications, v.25 n.1, p.5-15, January 2014
1017. Xiyan He, Gilles Mourot, Didier Maquin, José Ragot, Pierre Beauseroy, André Smolarz, Edith Grall-Maës, Multi-task Learning with One-class SVM, Neurocomputing, 133, p.416-426, June, 2014
1018. Vladimir Ceperic, Georges Gielen, Adrijan Baric, Sparse Ε-tube Support Vector Regression by Active Learning, Soft Computing - A Fusion of Foundations, Methodologies and Applications, v.18 n.6, p.1113-1126, June 2014
1019. Jianqiang Gao, Lizhong Xu, Aiye Shi, Fengchen Huang, A Kernel-based Block Matrix Decomposition Approach for the Classification of Remotely Sensed Images, Applied Mathematics and Computation, 228, p.531-545, February, 2014
1020. Samuel Epstein, Eric Missimer, Margrit Betke, Using Kernels for a Video-based Mouse-replacement Interface, Personal and Ubiquitous Computing, v.18 n.1, p.47-60, January 2014
1021. Yunlong Jiao, Jean-Philippe Vert, The Kendall and Mallows Kernels for Permutations, Proceedings of the 32nd International Conference on International Conference on Machine Learning, July 06-11, 2015, Lille, France
1022. Maurizio Filippone, Dealing with Non-metric Dissimilarities in Fuzzy Central Clustering Algorithms, International Journal of Approximate Reasoning, v.50 n.2, p.363-384, February, 2009
1023. Jan Verwaeren, Willem Waegeman, Bernard De Baets, Learning Partial Ordinal Class Memberships with Kernel-based Proportional Odds Models, Computational Statistics & Data Analysis, v.56 n.4, p.928-942, April, 2012
1024. Stergios Papadimitriou, Seferina Mavroudi, Spiridon Likothanassis, Mutual Information Clustering for Efficient Mining of Fuzzy Association Rules with Application to Gene Expression Data Analysis, Proceedings of the 9th WSEAS International Conference on Computers, p.1-9, July 14-16, 2005, Athens, Greece
1025. Ron Bekkerman, Ran El-Yaniv, Naftali Tishby, Yoad Winter, Distributional Word Clusters Vs. Words for Text Categorization, The Journal of Machine Learning Research, 3, 3/1/2003
1026. Tomáš Pevný, Jessica Fridrich, Benchmarking for Steganography, Information Hiding: 10th International Workshop, IH 2008, Santa Barbara, CA, USA, May 19-21, 2008, Revised Selected Papers, Springer-Verlag, Berlin, Heidelberg, 2008
1027. Gavin C. Cawley, Nicola L. Talbot, Efficient Approximate Leave-one-out Cross-validation for Kernel Logistic Regression, Machine Learning, v.71 n.2-3, p.243-264, June 2008
1028. Valeria Garro, Andrea Giachetti, TreeSha: 3D Shape Retrieval with a Tree Graph Representation based on the Autodiffusion Function Topology, Proceedings of the 7th Eurographics Workshop on 3D Object Retrieval, April 06-06, 2014, Strasbourg, France
1029. Deepak Chawla, Lin Li, Stephen Scott, On Approximating Weighted Sums with Exponentially Many Terms, Journal of Computer and System Sciences, v.69 n.2, p.196-234, September 2004
1030. Baharan Mirzasoleiman, Ashwinkumar Badanidiyuru, Amin Karbasi, Fast Constrained Submodular Maximization: Personalized Data Summarization, Proceedings of the 33rd International Conference on International Conference on Machine Learning, June 19-24, 2016, New York, NY, USA
1031. Oliver Kramer, Covariance Matrix Self-Adaptation and Kernel Regression - Perspectives of Evolutionary Optimization in Kernel Machines, Fundamenta Informaticae, v.98 n.1, p.87-106, January 2010
1032. Il Memming Park, Sohan Seth, Murali Rao, José C. Príncipe, Strictly Positive-definite Spike Train Kernels for Point-process Divergences, Neural Computation, v.24 n.8, p.2223-2250, August 2012
1033. Pedro J. García-Laencina, Pedro Henriques Abreu, Miguel Henriques Abreu, Noémia Afonoso, Missing Data Imputation on the 5-year Survival Prediction of Breast Cancer Patients with Unknown Discrete Values, Computers in Biology and Medicine, v.59 N.C, p.125-133, April 2015
1034. Nan Liu, Han Wang, Weighted Principal Component Extraction with Genetic Algorithms, Applied Soft Computing, v.12 n.2, p.961-974, February, 2012
1035. Martin L. Hazelton, Berwin A. Turlach, Nonparametric Density Deconvolution by Weighted Kernel Estimators, Statistics and Computing, v.19 n.3, p.217-228, September 2009
1036. Nick J. Pizzi, Witold Pedrycz, Aggregating Multiple Classification Results Using Fuzzy Integration and Stochastic Feature Selection, International Journal of Approximate Reasoning, v.51 n.8, p.883-894, October, 2010
1037. Ricardo Íanculef, Carlos Valle, Héctor Allende, Claudio Moraga, Training Regression Ensembles by Sequential Target Correction and Resampling, Information Sciences: An International Journal, 195, p.154-174, July, 2012
1038. André Henn, Christoph Römer, Gerhard Gröger, Lutz Plümer, Automatic Classification of Building Types in 3D City Models, Geoinformatica, v.16 n.2, p.281-306, April 2012
1039. Anirban Basudhar, Christoph Dribusch, Sylvain Lacaze, Samy Missoum, Constrained Efficient Global Optimization with Support Vector Machines, Structural and Multidisciplinary Optimization, v.46 n.2, p.201-221, August 2012
1040. Zhiyong Li, Ye Tian, Ke Li, Fanyin Zhou, Wei Yang, Reject Inference in Credit Scoring Using Semi-supervised Support Vector Machines, Expert Systems with Applications: An International Journal, v.74 N.C, p.105-114, May 2017
1041. Věra Kůrková, Marcello Sanguineti, Learning with Generalization Capability by Kernel Methods of Bounded Complexity, Journal of Complexity, v.21 n.3, p.350-367, June 2005
1042. Katarina Domijan, Simon P. Wilson, Bayesian Kernel Projections for Classification of High Dimensional Data, Statistics and Computing, v.21 n.2, p.203-216, April 2011
1043. Bac Nguyen, Carlos Morell, Bernard De Baets, Large-scale Distance Metric Learning for K-nearest Neighbors Regression, Neurocomputing, v.214 N.C, p.805-814, November 2016
1044. Věra Kuková, Marcello Sanguineti, Learning with Generalization Capability by Kernal Methods of Bounded Complexity, Journal of Complexity, v.21 n.3, p.350-367, June 2005
1045. Meiling Cai, Beiji Zou, Huanzhi Gao, Juan Song, Motion Recognition for 3D Human Motion Capture Data Using Support Vector Machines with Rejection Determination, Multimedia Tools and Applications, v.70 n.2, p.1333-1362, May 2014
1046. Lev V. Utkin, Yulia A. Zhuk, Imprecise Prior Knowledge Incorporating Into One-class Classification, Knowledge and Information Systems, v.41 n.1, p.53-76, October 2014
1047. Qinghua Hu, Shiguang Zhang, Zongxia Xie, Jusheng Mi, Jie Wan, Noise Model based Ν-support Vector Regression with Its Application to Short-term Wind Speed Forecasting, Neural Networks, 57, p.1-11, September, 2014
1048. Maciej Ławryńczuk, Modelling and Predictive Control of a Neutralisation Reactor Using Sparse Support Vector Machine Wiener Models, Neurocomputing, v.205 N.C, p.311-328, September 2016
1049. Sang Hoon Lee, Yunmook Nah, Lynn Choi, Influenza Surveillance and Forecast with Smartphone Sensors, Computing, v.97 n.3, p.237-259, March 2015
1050. Hà Quang Minh, Loris Bazzani, Vittorio Murino, A Unifying Framework in Vector-valued Reproducing Kernel Hilbert Spaces for Manifold Regularization and Co-regularized Multi-view Learning, The Journal of Machine Learning Research, v.17 n.1, p.769-840, January 2016
1051. Christian Eitzinger, W. Heidl, E. Lughofer, S. Raiser, J. E. Smith, M. A. Tahir, D. Sannen, H. Van Brussel, Assessment of the Influence of Adaptive Components in Trainable Surface Inspection Systems, Machine Vision and Applications, v.21 n.5, p.613-626, August 2010
1052. Jane Reilly, John Ghent, John McDonald, Investigating the Dynamics of Facial Expression, Proceedings of the Second International Conference on Advances in Visual Computing, p.334-343, November 06-08, 2006, Lake Tahoe, NV
1053. Sheng Chen, Xia Hong, Bing L. Luk, Chris J. Harris, Construction of Tunable Radial Basis Function Networks Using Orthogonal Forward Selection, IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, v.39 n.2, p.457-466, April 2009
1054. Alexandre G. Evsukoff, Sylvie Galichet, Beatriz S. L. P. De Lima, Nelson F. F. Ebecken, Design of Interpretable Fuzzy Rule-based Classifiers Using Spectral Analysis with Structure and Parameters Optimization, Fuzzy Sets and Systems, v.160 n.7, p.857-881, April, 2009
1055. A. Sanz-Garcia, J. Fernandez-Ceniceros, F. Antonanzas-Torres, A.V. Pernia-Espinoza, F.J. Martinez-de-Pison, GA-PARSIMONY, Applied Soft Computing, v.35 N.C, p.13-28, October 2015
1056. Lev V. Utkin, Anatoly I. Chekh, A New Robust Model of One-class Classification by Interval-valued Training Data Using the Triangular Kernel, Neural Networks, v.69 N.C, p.99-110, September 2015
1057. Xiaobo Chen, Jian Yang, Qiaolin Ye, Jun Liang, Recursive Projection Twin Support Vector Machine via Within-class Variance Minimization, Pattern Recognition, v.44 n.10-11, p.2643-2655, October, 2011
1058. Chung-Wei Liang, Chia-Feng Juang, Moving Object Classification Using Local Shape and HOG Features in Wavelet-transformed Space with Hierarchical SVM Classifiers, Applied Soft Computing, v.28 N.C, p.483-497, March 2015
1059. Christoph Römer, Kathrin Bürling, Mauricio Hunsche, Till Rumpf, Georg Noga, Lutz Plümer, Robust Fitting of Fluorescence Spectra for Pre-symptomatic Wheat Leaf Rust Detection with Support Vector Machines, Computers and Electronics in Agriculture, v.79 n.2, p.180-188, November, 2011
1060. Jaume Gibert, Ernest Valveny, Horst Bunke, Feature Selection on Node Statistics based Embedding of Graphs, Pattern Recognition Letters, v.33 n.15, p.1980-1990, November, 2012
1061. Chengjun Liu, Capitalize on Dimensionality Increasing Techniques for Improving Face Recognition Grand Challenge Performance, IEEE Transactions on Pattern Analysis and Machine Intelligence, v.28 n.5, p.725-737, May 2006
1062. Yan Zheng, Jeffrey Jestes, Jeff M. Phillips, Feifei Li, Quality and Efficiency for Kernel Density Estimates in Large Data, Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data, June 22-27, 2013, New York, New York, USA
1063. Yang Li, Li Guo, Yike Guo, Enabling Health Monitoring As a Service in the Cloud, Proceedings of the 2014 IEEE/ACM 7th International Conference on Utility and Cloud Computing, p.127-136, December 08-11, 2014
1064. Rui Ji, Yupu Yang, Weidong Zhang, Incremental Smooth Support Vector Regression for Takagi-Sugeno Fuzzy Modeling, Neurocomputing, 123, p.281-291, January, 2014
1065. Haim Avron, Vikas Sindhwani, Jiyan Yang, Michael W. Mahoney, Quasi-Monte Carlo Feature Maps for Shift-invariant Kernels, The Journal of Machine Learning Research, v.17 n.1, p.4096-4133, January 2016
1066. Afra Mashhadi, Utku Günay Acer, Aidan Boran, Philipp M. Scholl, Claudio Forlivesi, Geert Vanderhulst, Fahim Kawsar, Exploring Space Syntax on Entrepreneurial Opportunities with Wi-Fi Analytics, Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing, September 12-16, 2016, Heidelberg, Germany
1067. Roman Rosipal, Nicole Krämer, Overview and Recent Advances in Partial Least Squares, Proceedings of the 2005 International Conference on Subspace, Latent Structure and Feature Selection, February 23-25, 2005, Bohinj, Slovenia
1068. Shai Shalev-Shwartz, Online Learning and Online Convex Optimization, Foundations and Trends® in Machine Learning, v.4 n.2, p.107-194, February 2012
1069. Paul Honeine, Zineb Noumir, Cédric Richard, Multiclass Classification Machines with the Complexity of a Single Binary Classifier, Signal Processing, v.93 n.5, p.1013-1026, May, 2013
1070. Albert K. Feeny, Mongkol Tadarati, David E. Freund, Neil M. Bressler, Philippe Burlina, Automated Segmentation of Geographic Atrophy of the Retinal Epithelium via Random Forests in AREDS Color Fundus Images, Computers in Biology and Medicine, v.65 N.C, p.124-136, October 2015
1071. Maciej Kusy, Jacek Kluska, Assessment of Prediction Ability for Reduced Probabilistic Neural Network in Data Classification Problems, Soft Computing - A Fusion of Foundations, Methodologies and Applications, v.21 n.1, p.199-212, January 2017
1072. G. Asencio-Cortés, E. Florido, A. Troncoso, F. Martínez-Álvarez, A Novel Methodology to Predict Urban Traffic Congestion with Ensemble Learning, Soft Computing - A Fusion of Foundations, Methodologies and Applications, v.20 n.11, p.4205-4216, November 2016
1073. Thomas Burger, Geometric Views on Conflicting Mass Functions, International Journal of Approximate Reasoning, v.70 N.C, p.36-50, March 2016
1074. Gianluigi Pillonetto, A New Kernel-based Approach to Hybrid System Identification, Automatica (Journal of IFAC), v.70 N.C, p.21-31, August 2016
1075. Marco Signoretto, Lieven De Lathauwer, Johan A. K. Suykens, 2011 Special Issue: A Kernel-based Framework to Tensorial Data Analysis, Neural Networks, v.24 n.8, p.861-874, October, 2011
1076. Kamaledin Ghiasi-Shirazi, Reza Safabakhsh, Mostafa Shamsi, Learning Translation Invariant Kernels for Classification, The Journal of Machine Learning Research, 11, p.1353-1390, 3/1/2010
1077. Sepp Hochreiter, Klaus Obermayer, Support Vector Machines for Dyadic Data, Neural Computation, v.18 n.6, p.1472-1510, June 2006
1078. Kuo-Wei Hsu, Integrating Adaptive Boosting and Support Vector Machines with Varying Kernels, Proceedings of the 11th International Conference on Ubiquitous Information Management and Communication, p.1-8, January 05-07, 2017, Beppu, Japan
1079. Lev V. Utkin, Anatoly I. Chekh, Yulia A. Zhuk, Binary Classification SVM-based Algorithms with Interval-valued Training Data Using Triangular and Epanechnikov Kernels, Neural Networks, v.80 N.C, p.53-66, August 2016
1080. Filippo Maria Bianchi, Lorenzo Livi, Antonello Rizzi, Alireza Sadeghian, A Granular Computing Approach to the Design of Optimized Graph Classification Systems, Soft Computing - A Fusion of Foundations, Methodologies and Applications, v.18 n.2, p.393-412, February 2014
1081. Hwang Ho Kim, Jin Young Choi, Hierarchical Multi-class LAD based on OvA-binary Tree Using Genetic Algorithm, Expert Systems with Applications: An International Journal, v.42 n.21, p.8134-8145, November 2015
1082. Toke J. Hansen, Michael W. Mahoney, Semi-supervised Eigenvectors for Large-scale Locally-biased Learning, The Journal of Machine Learning Research, v.15 n.1, p.3691-3734, January 2014
1083. Abhijit Bose, Xin Hu, Kang G. Shin, Taejoon Park, Behavioral Detection of Malware on Mobile Handsets, Proceedings of the 6th International Conference on Mobile Systems, Applications, and Services, June 17-20, 2008, Breckenridge, CO, USA
1084. Jieping Ye, Shuiwang Ji, Jianhui Chen, Multi-class Discriminant Kernel Learning via Convex Programming, The Journal of Machine Learning Research, 9, p.719-758, 6/1/2008
1085. Pasquale De Meo, Antonino Nocera, Domenico Rosaci, Domenico Ursino, Recommendation of Reliable Users, Social Networks and High-quality Resources in a Social Internetworking System, AI Communications, v.24 n.1, p.31-50, January 2011
1086. Mark Everingham, Andrew Zisserman, Christopher K. I. Williams, Luc Van Gool, Moray Allan, Christopher M. Bishop, Olivier Chapelle, Navneet Dalal, Thomas Deselaers, Gyuri Dorkó, Stefan Duffner, Jan Eichhorn, Jason D. R. Farquhar, Mario Fritz, Christophe Garcia, Tom Griffiths, Frederic Jurie, Daniel Keysers, Markus Koskela, Jorma Laaksonen, Diane Larlus, Bastian Leibe, Hongying Meng, Hermann Ney, Bernt Schiele, Cordelia Schmid, Edgar Seemann, John Shawe-Taylor, Amos Storkey, Sandor Szedmak, Bill Triggs, Ilkay Ulusoy, Ville Viitaniemi, Jianguo Zhang, The 2005 PASCAL Visual Object Classes Challenge, Proceedings of the First International Conference on Machine Learning Challenges: Evaluating Predictive Uncertainty Visual Object Classification, and Recognizing Textual Entailment, p.117-176, April 11-13, 2005, Southampton, UK
1087. Nick J. Pizzi, Fuzzy Quartile Encoding As a Preprocessing Method for Biomedical Pattern Classification, Theoretical Computer Science, v.412 n.42, p.5909-5925, September, 2011
1088. Bernard Haasdonk, Hans Burkhardt, Invariant Kernel Functions for Pattern Analysis and Machine Learning, Machine Learning, v.68 n.1, p.35-61, July 2007
1089. Damiano Varagnolo, Gianluigi Pillonetto, Luca Schenato, Distributed Parametric and Nonparametric Regression with on-line Performance Bounds Computation, Automatica (Journal of IFAC), v.48 n.10, p.2468-2481, October, 2012
1090. Stefan Scherer, Michael Glodek, Friedhelm Schwenker, Nick Campbell, Günther Palm, Spotting Laughter in Natural Multiparty Conversations: A Comparison of Automatic Online and Offline Approaches Using Audiovisual Data, ACM Transactions on Interactive Intelligent Systems (TiiS), v.2 n.1, p.1-31, March 2012
1091. Keng-Pei Lin, Privacy-preserving Kernel K-means Clustering Outsourcing with Random Transformation, Knowledge and Information Systems, v.49 n.3, p.885-908, December 2016
1092. Song Liu, Makoto Yamada, Nigel Collier, Masashi Sugiyama, Change-point Detection in Time-series Data by Relative Density-ratio Estimation, Neural Networks, 43, p.72-83, July, 2013
1093. Sébastien Gadat, Laurent Younes, A Stochastic Algorithm for Feature Selection in Pattern Recognition, The Journal of Machine Learning Research, 8, p.509-547, 5/1/2007
1094. Mona Mahmoudi, Guillermo Sapiro, Three-dimensional Point Cloud Recognition via Distributions of Geometric Distances, Graphical Models, v.71 n.1, p.22-31, January, 2009
1095. Wei Wu, Jun Xu, Hang Li, Satoshi Oyama, Learning a Robust Relevance Model for Search Using Kernel Methods, The Journal of Machine Learning Research, 12, p.1429-1458, 2/1/2011
1096. Marcin Marszałek, Cordelia Schmid, Accurate Object Recognition with Shape Masks, International Journal of Computer Vision, v.97 n.2, p.191-209, April 2012
1097. J. Sánchez-Monedero, Pedro A. Gutiérrez, Peter Tiňo, C. Hervás-Martínez, Exploitation of Pairwise Class Distances for Ordinal Classification, Neural Computation, v.25 n.9, p.2450-2485, September 2013
1098. Jan Behmann, Kathrin Hendriksen, Ute Müller, Wolfgang Büscher, Lutz Plümer, Support Vector Machine and Duration-aware Conditional Random Field for Identification of Spatio-temporal Activity Patterns by Combined Indoor Positioning and Heart Rate Sensors, Geoinformatica, v.20 n.4, p.693-714, October 2016
1099. Isis Didier Lins, Moacyr Araujo, Márcio Das Chagas Moura, Marcus André Silva, Enrique López Droguett, Prediction of Sea Surface Temperature in the Tropical Atlantic by Support Vector Machines, Computational Statistics & Data Analysis, v.61 N.C, p.187-198, May 2013
1100. Isis Didier Lins, Moacyr Araujo, MáRcio Das Chagas Moura, Marcus André Silva, Enrique LóPez Droguett, Prediction of Sea Surface Temperature in the Tropical Atlantic by Support Vector Machines, Computational Statistics & Data Analysis, 61, p.187-198, May, 2013
1101. V. Ceperic, G. Gielen, A. Baric, Recurrent Sparse Support Vector Regression Machines Trained by Active Learning in the Time-domain, Expert Systems with Applications: An International Journal, v.39 n.12, p.10933-10942, September, 2012
1102. Chengjun Liu, Gabor-Based Kernel PCA with Fractional Power Polynomial Models for Face Recognition, IEEE Transactions on Pattern Analysis and Machine Intelligence, v.26 n.5, p.572-581, May 2004
1103. Imed Laaridh, Corinne Fredouille, Christine Meunier, Automatic Detection of Phone-Based Anomalies in Dysarthric Speech, ACM Transactions on Accessible Computing (TACCESS), v.6 n.3, June 2015
1104. Junchen Jiang, Vyas Sekar, Henry Milner, Davis Shepherd, Ion Stoica, Hui Zhang, CFA: A Practical Prediction System for Video QoE Optimization, Proceedings of the 13th Usenix Conference on Networked Systems Design and Implementation, p.137-150, March 16-18, 2016, Santa Clara, CA
1105. Erik Rodner, Alexander Freytag, Paul Bodesheim, Björn Fröhlich, Joachim Denzler, Large-Scale Gaussian Process Inference with Generalized Histogram Intersection Kernels for Visual Recognition Tasks, International Journal of Computer Vision, v.121 n.2, p.253-280, January 2017
1106. P.J. García Nieto, E. García-Gonzalo, J.R. Alonso Fernández, C. Díaz Muñiz, A Hybrid PSO Optimized SVM-based Model for Predicting a Successful Growth Cycle of the Spirulina Platensis from Raceway Experiments Data, Journal of Computational and Applied Mathematics, v.291 N.C, p.293-303, January 2016
1107. Hong-Ying Yang, Xian-Jin Zhang, Xiang-Yang Wang, LS-SVM-based Image Segmentation Using Pixel Color-texture Descriptors, Pattern Analysis & Applications, v.17 n.2, p.341-359, May 2014
1108. Yiguang Liu, Xiaochun Cao, Jian Guo Liu, Classification Using Distances from Samples to Linear Manifolds, Pattern Analysis & Applications, v.16 n.3, p.417-430, August 2013
1109. Tao Xiong, Chongguang Li, Yukun Bao, Zhongyi Hu, Lu Zhang, A Combination Method for Interval Forecasting of Agricultural Commodity Futures Prices, Knowledge-Based Systems, v.77 N.C, p.92-102, March 2015
1110. Min-Yuan Cheng, Andreas F. V. Roy, Evolutionary Fuzzy Decision Model for Construction Management Using Support Vector Machine, Expert Systems with Applications: An International Journal, v.37 n.8, p.6061-6069, August, 2010
1111. Gaya K. Jayasinghe, J. Shane Culpepper, Peter Bertok, Efficient and Effective Realtime Prediction of Drive-by Download Attacks, Journal of Network and Computer Applications, 38, p.135-149, February, 2014
1112. Zhikun Wang, Katharina Mülling, Marc Peter Deisenroth, Heni Ben Amor, David Vogt, Bernhard Schölkopf, Jan Peters, Probabilistic Movement Modeling for Intention Inference in Human-robot Interaction, International Journal of Robotics Research, v.32 n.7, p.841-858, June 2013
1113. Kristen Fortney, Douglas B. Tweed, Computational Advantages of Reverberating Loops for Sensorimotor Learning, Neural Computation, v.24 n.3, p.611-634, March 2012
1114. Jun Wang, Arjen P. De Vries, Marcel J. T. Reinders, Unified Relevance Models for Rating Prediction in Collaborative Filtering, ACM Transactions on Information Systems (TOIS), v.26 n.3, p.1-42, June 2008
1115. Kensuke Fukuda, John Heidemann, Detecting Malicious Activity with DNS Backscatter, Proceedings of the 2015 ACM Conference on Internet Measurement Conference, October 28-30, 2015, Tokyo, Japan
1116. Saman Bashbaghi, Eric Granger, Robert Sabourin, Guillaume-Alexandre Bilodeau, Robust Watch-list Screening Using Dynamic Ensembles of SVMs based on Multiple Face Representations, Machine Vision and Applications, v.28 n.1-2, p.219-241, February 2017
1117. Bartosz Krawczyk, Michał Woźniak, One-class Classifiers with Incremental Learning and Forgetting for Data Streams with Concept Drift, Soft Computing - A Fusion of Foundations, Methodologies and Applications, v.19 n.12, p.3387-3400, December 2015
1118. Andreas Christmann, Ding-Xuan Zhou, On the Robustness of Regularized Pairwise Learning Methods based on Kernels, Journal of Complexity, v.37 N.C, p.1-33, December 2016
1119. Ashish Shrivastava, Vishal M. Patel, Jaishanker K. Pillai, Rama Chellappa, Generalized Dictionaries for Multiple Instance Learning, International Journal of Computer Vision, v.114 n.2-3, p.288-305, September 2015
1120. Nicola Segata, Enrico Blanzieri, Operators for Transforming Kernels Into Quasi-local Kernels That Improve SVM Accuracy, Journal of Intelligent Information Systems, v.37 n.2, p.155-186, October 2011
1121. Giorgio Gnecco, Marcello Sanguineti, Regularization Techniques and Suboptimal Solutions to Optimization Problems in Learning from Data, Neural Computation, v.22 n.3, p.793-829, March 2010
1122. Shantanu Chakrabartty, Gert Cauwenberghs, Gini Support Vector Machine: Quadratic Entropy Based Robust Multi-Class Probability Regression, The Journal of Machine Learning Research, 8, p.813-839, 5/1/2007
1123. D. Malchiodi, An Experimental Analysis of the Impact of Accuracy Degradation in SVM Classification, International Journal of Computational Intelligence Studies, v.1 n.2, p.163-190, February 2009
1124. Aykut Erdem, Sibel Tari, A Similarity-based Approach for Shape Classification Using Aslan Skeletons, Pattern Recognition Letters, v.31 n.13, p.2024-2032, October, 2010
1125. Weiran Wang, Raman Arora, Karen Livescu, Jeff Bilmes, On Deep Multi-view Representation Learning, Proceedings of the 32nd International Conference on International Conference on Machine Learning, July 06-11, 2015, Lille, France
1126. Libin Duan, Guangyong Sun, Junjia Cui, Tao Chen, Aiguo Cheng, Guangyao Li, Crashworthiness Design of Vehicle Structure with Tailor Rolled Blank, Structural and Multidisciplinary Optimization, v.53 n.2, p.321-338, February 2016
1127. Yonggang Yao, Yoonkyung Lee, Another Look at Linear Programming for Feature Selection via Methods of Regularization, Statistics and Computing, v.24 n.5, p.885-905, September 2014
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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2001 LearningWithKernels	Bernhard Schölkopf Alexander J. Smola			Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond