Ron Kohavi

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Ron Kohavi is a person.

See: Cross-Validation, Feature Selection Algorithm, CUPED.

References

2024

(Kohavi & Chen, 2024) ⇒ Ron Kohavi, and Nanyu Chen. (2024). “False Positives in A/B Tests.” doi:10.1145/3637528.3671631

2013

(Kohavi et al., 2013) ⇒ Ron Kohavi, Alex Deng, Brian Frasca, Toby Walker, Ya Xu, and Nils Pohlmann. (2013). “Online Controlled Experiments at Large Scale.” In: Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. doi:10.1145/2487575.2488217
(Deng et al., 2013) ⇒ Alex Deng, Ya Xu, Ron Kohavi, and Toby Walker. (2013). “Improving the Sensitivity of Online Controlled Experiments by Utilizing Pre-experiment Data.” In: Proceedings of the sixth ACM International Conference on Web search and data mining, pp. 123-132.

2012

(Kohavi et al., 2012) ⇒ Ron Kohavi, Alex Deng, Brian Frasca, Roger Longbotham, Toby Walker, and Ya Xu. (2012). “Trustworthy Online Controlled Experiments: Five Puzzling Outcomes Explained.” In: Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. doi:10.1145/2339530.2339653

2009

(Crook et al., 2009) ⇒ Thomas Crook, Ron Kohavi, Roger Longbotham, and Brian Frasca. (2009). “Seven Pitfalls to Avoid when Running Controlled Experiments on the Web.” In: Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2009). doi:10.1145/1557019.1557139
(Kohavi et al., 2009) ⇒ Ron Kohavi, Roger Longbotham, Dan Sommerfield, and Randal M. Henne, (2009). “Controlled Experiments on the Web: survey and practical guide.” In: Data Mining and Knowledge Discovery, 18(1). doi:10.1007/s10618-008-0114-1

2007

(Kohavi et al., 2007) ⇒ Ron Kohavi, Randal M. Henne, and Dan Sommerfield. (2007). “Practical Guide to Controlled Experiments on the Web: Listen to Your Customers Not to the Hippo.” In: Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. doi:10.1145/1281192.1281295

1999

(Bauer & Kohavi, 1999) ⇒ Eric Bauer, and Ron Kohavi. (1999). “An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting and Variants.” In: Machine Learning, 36(1-2).

1998

(Kohavi & Provost, 1998) ⇒ Ron Kohavi, and Foster Provost. (1998). “Glossary of Terms.” In: Editorial for the Special Issue on Applications of Machine Learning and the Knowledge Discovery Process, Machine Leanring 30(2-3).
(Provost et al., 1998) ⇒ Foster Provost, Tom Fawcett, and Ron Kohavi. (1998). “The Case Against Accuracy Estimation for Comparing Induction Algorithms.” In: Proceedings of the Fifteenth International Conference on Machine Learning (ICML 1998).

1997

(Kohavi & John, 1997) ⇒ Ron Kohavi, and George John. “Wrappers for Feature Selection.” In: Artificial Intelligence, 97(1). doi:10.1016/S0004-3702(97)00043-X

1996

(Kohavi & Wolpert, 1996) ⇒ Ron Kohavi, and David Wolpert. (1996). “Bias Plus Variance Decomposition for Zero-One Loss Functions.” In: Proceedings of the 13th International Conference on Machine Learning (ICML 1996).
- Slides: http://robotics.stanford.edu/%7Eronnyk/biasVar-slides.ps.Z
(Kohavi et al., 1996) ⇒ Ron Kohavi, Dan Sommerfield, James Dougherty. (1996) Data Mining using MLC++, A Machine Learning Library in C++.” In: Proceedings of the 8th International Conference on Tools with Artificial Intelligence (ICTAI 1996).
(Friedman et al., 1996) ⇒ Jerome H. Friedman, Ron Kohavi, and Yeogirl Yun. (1996). “Lazy Decision Trees.” In: Proceedings of the Thirteenth National Conference on Artificial Intelligence (AAAI 1996).

1995

(Kohavi, 1995) ⇒ Ron Kohavi. (1995). “A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection.” In: Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence (IJCAI 1995).

1994

(John et al., 1994) ⇒ George H. John, Ron Kohavi, and Karl Pfleger (1994). “Irrelevant Features and the Subset Selection Problem.” In: Proceedings of the Eleventh International Conference on Machine Learning (ICML 1994).

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