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