Active Bibliography

papers/159 Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data – John Lafferty, Andrew Mccallum, O C. N. Pereira, John Lafferty
336 Shallow Parsing with Conditional Random Fields – Fei Sha, Fernando Pereira - 2003
A Review of Sequential Supervised Learning – Guohua Hao - 2004
1 A review of RKHS methods in machine learning – Thomas Hofmann, Bernhard Schölkopf, Alexander J. Smola - 2006
27 A tutorial on energy-based learning – Yann Lecun, Sumit Chopra, Raia Hadsell, Fu Jie Huang, G. Bakir, T. Hofman, B. Schölkopf, A. Smola, B. Taskar (eds - 2006
393 Dynamic Bayesian Networks: Representation, Inference and Learning – Kevin Patrick Murphy - 2002
3 An introduction to structured discriminative learning – Roland Memisevic - 2006
unknown title – unknown authors
Distributed Generative . . . – n.n.
1 Information Extraction: Methodologies and Applications – Jie Tang, Mingcai Hong, Duo Zhang, Bangyong Liang, Juanzi Li, Jie Tang (corresponding, Mingcai Hong, Duo Zhang, Juanzi Li, Jie Tang, Mingcai Hong, Duo Zhang, Bangyong Liang, Juanzi Li
142 Efficiently Inducing Features of Conditional Random Fields – Andrew McCallum - 2003
1 Learning semantic parsers using statistical syntactic parsing techniques. Doctoral Dissertation Proposal – Ruifang Ge - 2006
34 Conditional random fields: An introduction – Hanna M. Wallach - 2004
7 Maximum Entropy Methods for Biological Sequence Modeling – Eugen C. Buehler, Lyle H. Ungar - 2001
18 A Review of Kernel Methods in Machine Learning – Thomas Hofmann, Bernhard Schölkopf, Alexander J. Smola - 2006
12 Joint and Conditional Estimation of Tagging and Parsing Models – Mark Johnson - 2001
2 Discriminative Methods for Label Sequence Learning – Yasemin Altun - 2005
5 Active Learning for Logistic Regression – Andrew Ian Schein - 2005
22 Probabilistic Models for Query Approximation with Large Sparse Binary Data Sets – Dmitry Pavlov, Heikki Mannila, Padhraic Smyth - 2000