28th February 2005 — Conditional Random Fields
Chu Wei and Fernando will review Conditional Random Fields (CRFs).
Two short conference papers are:
A good tutorial presentation with examples and other approaches is:
- Thomas G. Dietterich. Machine Learning for Sequential Data: A Review. In Structural, Syntactic, and Statistical Pattern Recognition; Lecture Notes in Computer Science, Vol. 2396, T. Caelli (Ed.), pp. 15--30, Springer-Verlag, 2002. [pdf]
They also used the following papers:
- Yasemin Altun, Ioannis Tsochantaridis and Thomas Hofmann. Hidden Markov Support Vector Machines. In Proceedings of the Twentieth International Conference on Machine Learning (ICML 2003), 2003. [pdf]
- John Lafferty, Xiaojin Zhu and Yan Liu. Kernel conditional random fields: representation and clique selection. In Proceedings of the Twenty-First International Conference on Machine Learning (ICML 2004), 2004. [pdf]
- Yasemin Altun, Alex J. Smola, Thomas Hofmann. Exponential Families for Conditional Random Fields. In Proceedings of the 20th Conference on Uncertainty in Artificial Intelligence (UAI-2004), 2004. [pdf]
- Yasemin Altun, Thomas Hofmann and Alexander J. Smola. Gaussian process classification for segmenting and annotating sequences. In Proceedings of the Twenty-First International Conference on Machine Learning (ICML 2004), 2004. [pdf]
- Yuan Qi, Martin Szummer and Thomas P. Minka. Bayesian Conditional Random Fields. To appear in Proceedings of the Tenth International W\orkshop on Artificial Intelligence and Statistics (AISTATS 2005), 2005. [pdf]
This CRF page has many references and other resources.