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  1. 2008.02.14 Generative and Discriminative Approaches for Graphical Models
Machine Learning | Posted by 알 수 없는 사용자 2008. 2. 14. 16:53

Generative and Discriminative Approaches for Graphical Models

CRF and Perceptron approaches

[LafMcCPer01]
 Authors: John Lafferty, Andrew McCallum, Fernando Pereira
Title: Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data.
Proceedings: International Conference on Machine Learning (ICML-2001), 2001.
Presenter:Karthik

[LafZhuLiu04]
 Authors: John Lafferty, Xiaojin Zhu, Yan Liu
Title: Kernel Conditional Random Fields: Representation and Clique Selection
Proceedings: International Conference on Machine Learning (ICML-2004), 2004.
Presenter:Karthik

[Collins02]
Author: Michael Collins
Title: Discriminative Training Methods for Hidden Markov Models: Theory and Experiments with Perceptron Algorithms.
Proceedings: EMNLP 2002.
Presenter: Ozgur

SVM approaches

[TsoJoaHofAlt05]
 Authors: I. Tsochantaridis, T. Joachims, T. Hofmann, and Y. Altun
Title: Large Margin Methods for Structured and Interdependent Output Variables,
Journal: Journal of Machine Learning Research (JMLR), 6(Sep):1453-1484, 2005.
Presenter: Vikas

[TasGueKol04]
 Authors: Ben Taskar, Carlos Guestrin and Daphne Koller
Title: Max-Margin Markov Networks.
Proceedings: In Advances in Neural Information Processing Systems 16 (NIPS 2003), 2004.
Presenter: Irina

[McAllester06]
Authors: David McAllester
Generalization Bounds and Consistency for Structured Labeling
to appear in Predicting Structured Data,
edited by G. BakIr, T. Hofmann, B. Scholkopf, A. Smola, B. Taskar, and S. V. N. Vishwanathan. 2006
MIT Press.
Presenter: David


Boosting Approaches

[AltHofJoh03]
Authors: Yasemin Altun, Thomas Hofmann & Mark Johnson
Title: Discriminative Learning for Label Sequences via Boosting
Proceedings: Advances in Neural Information Processing Systems (NIPS*15), 2003.
Presenter: Ozgur

[TorMurFre05]
Authors: Antonio Torralba, Kevin Murphy and William Freeman
Title: Contextual Models for Object Detection using Boosted Random Fields
Proceedings: Advances in Neural Information Processing Systems (NIPS*17), 2005.
Presenter: Allie

[Collins04]
Authors: Michael Collins
Title: Discriminative Reranking for Natural Language Parsing.
Proceedings: International Conference on Machine Learning (ICML-2000), 2000.
Presenter: Irina


Decompositional Approaches

[DauMar05]
 Authors: Hal Daume and Daniel Marcu
Title: Learning as Search Optimization: Approximate Large Margin Methods for Structured Prediction
Proceedings: International Conference on Machine Learning (ICML), 2005.
Presenter: Yasemin

[RotYih05]
Authors: D. Roth and W. Yih
Title: Integer Linear Programming Inference for Conditional Random Fields.
Proceedings: International Conference on Machine Learning (ICML)  (2005) pp. 737--744
Presenter: Karthik

[LeCHua05]
Authors: LeCun and Huang
Title: Loss Functions for Discriminative Training of Energy-Based Models
Proceedings: AI-Stats, 2005
Presenter: Allie

[WesChaEliSchVap02]
Authors: J. Weston, O. Chapelle, A. Elisseeff, B. Schoelkopf and V. Vapnik
Title: Kernel Dependency Estimation
Proceedings: NIPS 2002.
Presenter: Vikas

Semi-Supervised/Unsupervised Learning

[AltMcCBel05]
Authors: Yasemin Altun, David McAllester, Misha Belkin.
Title: Maximum Margin Semi-Supervised Learning for Structured Variables
Proceedings: NIPS 2005.

[BreSch06]
Authors: Ulf Brefeld, Tobias Scheffer.
Title: Semi-Supervised Learning for Structured Output Variables,
Proceedings: ICML 2006.

[XuWilSouSch06]
Authors: Linli Xu, Dana Wilkinson, Finnegan Southey, Dale Schuurmans
Title: Discriminative Unsupervised Learning of Structured Predictors
Proceedings: ICML 2006.


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