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All publications by Lawrence K. Saul
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A Variational Approximation for Topic Modeling of Hierarchical Corpora
Do-kyum Kim, Geoffrey Voelker and Lawrence K. Saul
Proceedings of the 30th International Conference on Machine Learning (ICML-13), 2013


Latent Coincidence Analysis: A Hidden Variable Model for Distance Metric Learning
Matthew Der and Lawrence K. Saul
Advances in Neural Information Processing Systems 25, 2012


Maximum Covariance Unfolding : Manifold Learning for Bimodal Data
Vijay Mahadevan, Chi W. Wong, Jose C. Pereira, Tom Liu, Nuno Vasconcelos and Lawrence K. Saul
Advances in Neural Information Processing Systems 24, 2011


Hidden-Unit Conditional Random Fields
Laurens Maaten, Max Welling and Lawrence K. Saul
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics (AISTATS-11), 2011


Latent Variable Models for Predicting File Dependencies in Large-Scale Software Development
Diane Hu, Laurens Maaten, Youngmin Cho, Sorin Lerner and Lawrence K. Saul
Advances in Neural Information Processing Systems 23, 2010


Exploiting Feature Covariance in High-Dimensional Online Learning
Justin Ma, Alex Kulesza, Mark Dredze, Koby Crammer, Lawrence K. Saul and Fernando Pereira
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Distance Metric Learning for Large Margin Nearest Neighbor Classification
Kilian Q. Weinberger and Lawrence K. Saul
Journal of Machine Learning Research, 2009


Identifying suspicious URLs: an application of large-scale online learning
Justin Ma, Lawrence K. Saul, Stefan Savage and Geoffrey M. Voelker
Proceedings of the 26th International Conference on Machine Learning (ICML-09), 2009


Learning dictionaries of stable autoregressive models for audio scene analysis
Youngmin Cho and Lawrence K. Saul
Proceedings of the 26th International Conference on Machine Learning (ICML-09), 2009


Matrix updates for perceptron training of continuous density hidden Markov models
Chih-chieh Cheng, Fei Sha and Lawrence K. Saul
Proceedings of the 26th International Conference on Machine Learning (ICML-09), 2009


Kernel Methods for Deep Learning
Youngmin Cho and Lawrence K. Saul
Advances in Neural Information Processing Systems 22, 2009


Fast solvers and efficient implementations for distance metric learning
Kilian Q. Weinberger and Lawrence K. Saul
Proceedings of the 25th International Conference on Machine Learning (ICML-08), 2008


Graph Laplacian Regularization for Large-Scale Semidefinite Programming
Kilian Q. Weinberger, Fei Sha, Qihui Zhu and Lawrence K. Saul
Advances in Neural Information Processing Systems 19, 2006


Large Margin Hidden Markov Models for Automatic Speech Recognition
Fei Sha and Lawrence K. Saul
Advances in Neural Information Processing Systems 19, 2006


Analysis and extension of spectral methods for nonlinear dimensionality reduction
Fei Sha and Lawrence K. Saul
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Distance Metric Learning for Large Margin Nearest Neighbor Classification
Kilian Q. Weinberger, John Blitzer and Lawrence K. Saul
Advances in Neural Information Processing Systems 18, 2005


Learning a kernel matrix for nonlinear dimensionality reduction
Kilian Q. Weinberger, Fei Sha and Lawrence K. Saul
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Hierarchical Distributed Representations for Statistical Language Modeling
John Blitzer, Fernando Pereira, Kilian Q. Weinberger and Lawrence K. Saul
Advances in Neural Information Processing Systems 17, 2004


Real-Time Pitch Determination of One or More Voices by Nonnegative Matrix Factorization
Fei Sha and Lawrence K. Saul
Advances in Neural Information Processing Systems 17, 2004


Think Globally, Fit Locally: Unsupervised Learning of Low Dimensional Manifold
Lawrence K. Saul and Sam T. Roweis
Journal of Machine Learning Research, 2003


Real Time Voice Processing with Audiovisual Feedback: Toward Autonomous Agents with Perfect Pitch
Lawrence K. Saul, Daniel D. Lee, Charles L. Isbell and Yann L. Cun
Advances in Neural Information Processing Systems 15, 2002


Multiplicative Updates for Nonnegative Quadratic Programming in Support Vector Machines
Fei Sha, Lawrence K. Saul and Daniel D. Lee
Advances in Neural Information Processing Systems 15, 2002


Multiplicative Updates for Classification by Mixture Models
Lawrence K. Saul and Daniel D. Lee
Advances in Neural Information Processing Systems 14, 2001


Global Coordination of Local Linear Models
Sam T. Roweis, Lawrence K. Saul and Geoffrey E. Hinton
Advances in Neural Information Processing Systems 14, 2001