Max-Margin Markov Network Family
(Redirected from Maximum-Margin Markov Networks)
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.
- It can be instantiated in a Max-Margin Markov Network.
- See: Semi-Supervised Learning Algorithm, Support Vector Machine.
- (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 (SVMstruct), Max Margin Markov Networks (M3N),
- (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).