Recent advances in active learning
Sanjoy Dasgupta

Online learning of large margin hidden Markov models for automatic speech recognition
Lawrence Saul, Chih-Chieh Cheng, Fei Sha

On the role of machine learning in NLP
Eduard Hovy

Bayesian sensing hidden Markov models for speech recognition
George Saon, Jen-Tzung Chien

A non-parametric Bayesian approach to inflectional morphology
Jason Eisner, Markus Dreyer

Unlabeled data and other marginals
Mark Hasegawa-Johnson, Jui-Ting Huang, Xiaodan Zhuang

Structured prediction with indirect supervision
Ming-Wei Chang, James Clarke, Dan Goldwasser, Lev Ratinov, Vivek Srikumar, Dan Roth

Applications of submodular functions in speech and NLP
Jeff Bilmes, Hui Lin, Andrew Guillory

Generalization bounds and consistency for latent-structural probit and ramp loss
David McAllester

Some open problems in machine learning for NLP
Mark Steedman

Performance prediction and shrinking language models
Stanley Chen, Stephen Chu, Ahmad Emami, Lidia Mangu, Bhuvana Ramabhadran, Ruhi Sarikaya, Abhinav Sethy

On learning distributed representations of semantics
Yoshua Bengio

L1 and L2 regularization for multiclass hinge loss models
Robert Moore, John DeNero

A comparison of performance monitoring approaches to fusing spectrogram channels in speech recognition
Shirin Badiezadegan, Richard Rose

A two-layer non-negative matrix factorization model for vocabulary discovery
Meng Sun, Hugo Van hamme

Automating the scoring of elicited imitation tests
Deryle Lonsdale, Carl Christensen

Improving cross-document co-reference with semi-supervised information extraction modelsi
Rushin Shah, Bo Lin, Kevin Dela Rosa, Anatole Gershman, Robert Frederking

Panning for gold: finding relevant semantic content for grounded language learning
David Chen, Raymond Mooney

Performance monitoring for robustness in automatic recognition of speechi
Hynek Hermansky, Nima Mesgarani, Samuel Thomas