Max-Margin Markov Network Family

A Max-Margin Markov Network Family is a Markov Network Family/Markov Network Metamodel that incorporate kernels (to efficiently deal with high-dimensional features, and the ability to capture Correlations in structured data).

• AKA: Maximum-Margin Markov Networks.
• Context:
  • It can be instantiated in a Max-Margin Markov Network.
  • …
• Counter-Example(s):
  • a Conditional Random Fields.
• See: Semi-Supervised Learning Algorithm, Support Vector Machine.

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References

2007

• (Nguyen et al., 2007) ⇒ Nam Nguyen, and Yunsong Guo. (2007). “Comparisons of Sequence Labeling Algorithms and Extensions.” In: Proceedings of the 24th International Conference on Machine learning. doi:10.1145/1273496.1273582
  • QUOTE: In this paper, we survey the current state-of-art models for structured learning problems, including Hidden Markov Model (HMM), Conditional Random Fields (CRF), Averaged Perceptron (AP), Structured SVMs (SVM^struct), Max Margin Markov Networks (M³N),

2004

• (Taskar et al., 2004) ⇒ Ben Taskar, Carlos Guestrin, and Daphne Koller. (2004). “Max-Margin Markov Networks.” In: Advances in Neural Information Processing Systems (NIPS 2004).

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