Now showing items 21-27 of 27

    • Principal differences analysis: Interpretable characterization of differences between distributions 

      Mueller, Jonas Weylin; Jaakkola, Tommi S (Neural Information Processing Systems Foundation, Inc., 2015-12)
      We introduce principal differences analysis (PDA) for analyzing differences between high-dimensional distributions. The method operates by finding the projection that maximizes the Wasserstein divergence between the resulting ...
    • Steps to Excellence: Simple Inference with Refined Scoring of Dependency Trees 

      Zhang, Yuan; Lei, Tao; Barzilay, Regina; Jaakkola, Tommi S.; Globerson, Amir (Association for Computational Linguistics, 2014-06)
      Much of the recent work on dependency parsing has been focused on solving inherent combinatorial problems associated with rich scoring functions. In contrast, we demonstrate that highly expressive scoring functions can be ...
    • Tree block coordinate descent for map in graphical models 

      Sontag, David Alexander; Jaakkola, Tommi S. (Journal of Machine Learning Research, 2009-04)
      A number of linear programming relaxations have been proposed for finding most likely settings of the variables (MAP) in large probabilistic models. The relaxations are often succinctly expressed in the dual and reduce to ...
    • Two-sided exponential concentration bounds for Bayes error rate and Shannon entropy 

      Honorio, Jean; Jaakkola, Tommi S. (Association for Computing Machinery (ACM), 2013)
      We provide a method that approximates the Bayes error rate and the Shannon entropy with high probability. The Bayes error rate approximation makes possible to build a classifier that polynomially approaches Bayes error ...
    • A unified framework for consistency of regularized loss minimizers 

      Honorio, Jean; Jaakkola, Tommi S. (Association for Computing Machinery (ACM), 2014)
      We characterize a family of regularized loss minimization problems that satisfy three properties: scaled uniform convergence, super-norm regularization, and norm-loss monotonicity. We show several theoretical guarantees ...
    • An unsupervised method for uncovering morphological chains 

      Narasimhan, Karthik Rajagopal; Barzilay, Regina; Jaakkola, Tommi S. (Association for Computational Linguistics, 2015-03)
      Most state-of-the-art systems today produce morphological analysis based only on orthographic patterns. In contrast, we propose a model for unsupervised morphological analysis that integrates orthographic and semantic views ...
    • Validation and refinement of gene-regulatory pathways on a network of physical interactions 

      Yeang, Chen-Hsiang, 1969-; Mak, Craig; McCuine, Scott; Workman, Christopher; Ideker, Trey; e.a. (BioMed Central Ltd, 2005-07)
      As genome-scale measurements lead to increasingly complex models of gene regulation, systematic approaches are needed to validate and refine these models. Towards this goal, we describe an automated procedure for prioritizing ...