NIPS Proceedingsβ

Tommi Jaakkola

18 Papers

  • From random walks to distances on unweighted graphs (2015)
  • Principal Differences Analysis: Interpretable Characterization of Differences between Distributions (2015)
  • Controlling privacy in recommender systems (2014)
  • Learning Efficient Random Maximum A-Posteriori Predictors with Non-Decomposable Loss Functions (2013)
  • On Sampling from the Gibbs Distribution with Random Maximum A-Posteriori Perturbations (2013)
  • Active Information Retrieval (2001)
  • Partially labeled classification with Markov random walks (2001)
  • Tree-based reparameterization for approximate inference on loopy graphs (2001)
  • Kernel Expansions with Unlabeled Examples (2000)
  • Sequentially Fitting ``Inclusive'' Trees for Inference in Noisy-OR Networks (2000)
  • Maximum Entropy Discrimination (1999)
  • Exploiting Generative Models in Discriminative Classifiers (1998)
  • Approximating Posterior Distributions in Belief Networks Using Mixtures (1997)
  • Recursive Algorithms for Approximating Probabilities in Graphical Models (1996)
  • Fast Learning by Bounding Likelihoods in Sigmoid Type Belief Networks (1995)
  • Reinforcement Learning Algorithm for Partially Observable Markov Decision Problems (1994)
  • Reinforcement Learning with Soft State Aggregation (1994)
  • Convergence of Stochastic Iterative Dynamic Programming Algorithms (1993)