NIPS Proceedingsβ

Lawrence K. Saul

22 Papers

  • Latent Coincidence Analysis: A Hidden Variable Model for Distance Metric Learning (2012)
  • Maximum Covariance Unfolding : Manifold Learning for Bimodal Data (2011)
  • Latent Variable Models for Predicting File Dependencies in Large-Scale Software Development (2010)
  • Kernel Methods for Deep Learning (2009)
  • Graph Laplacian Regularization for Large-Scale Semidefinite Programming (2006)
  • Large Margin Hidden Markov Models for Automatic Speech Recognition (2006)
  • Distance Metric Learning for Large Margin Nearest Neighbor Classification (2005)
  • Hierarchical Distributed Representations for Statistical Language Modeling (2004)
  • Real-Time Pitch Determination of One or More Voices by Nonnegative Matrix Factorization (2004)
  • Multiplicative Updates for Nonnegative Quadratic Programming in Support Vector Machines (2002)
  • Real Time Voice Processing with Audiovisual Feedback: Toward Autonomous Agents with Perfect Pitch (2002)
  • Global Coordination of Local Linear Models (2001)
  • Multiplicative Updates for Classification by Mixture Models (2001)
  • Periodic Component Analysis: An Eigenvalue Method for Representing Periodic Structure in Speech (2000)
  • Inference in Multilayer Networks via Large Deviation Bounds (1998)
  • Markov Processes on Curves for Automatic Speech Recognition (1998)
  • Modeling Acoustic Correlations by Factor Analysis (1997)
  • A Variational Principle for Model-based Morphing (1996)
  • Hidden Markov Decision Trees (1996)
  • Exploiting Tractable Substructures in Intractable Networks (1995)
  • Fast Learning by Bounding Likelihoods in Sigmoid Type Belief Networks (1995)
  • Boltzmann Chains and Hidden Markov Models (1994)
  • 2 Books

  • Advances in Neural Information Processing Systems 17 (2004)
  • Advances in Neural Information Processing Systems 16 (2003)