NIPS Proceedingsβ

Pascal Poupart

13 Papers

  • Deep Homogeneous Mixture Models: Representation, Separation, and Approximation (2018)
  • Monte-Carlo Tree Search for Constrained POMDPs (2018)
  • Online Structure Learning for Feed-Forward and Recurrent Sum-Product Networks (2018)
  • Unsupervised Video Object Segmentation for Deep Reinforcement Learning (2018)
  • A Unified Approach for Learning the Parameters of Sum-Product Networks (2016)
  • Online Bayesian Moment Matching for Topic Modeling with Unknown Number of Topics (2016)
  • Cost-Sensitive Exploration in Bayesian Reinforcement Learning (2012)
  • Symbolic Dynamic Programming for Continuous State and Observation POMDPs (2012)
  • Automated Refinement of Bayes Networks' Parameters based on Test Ordering Constraints (2011)
  • Automated Hierarchy Discovery for Planning in Partially Observable Environments (2006)
  • VDCBPI: an Approximate Scalable Algorithm for Large POMDPs (2004)
  • Bounded Finite State Controllers (2003)
  • Value-Directed Compression of POMDPs (2002)