Maxime Chambreuil

Saturday April 17, 2004

Probabilistic Reasoning in AI

Max @ 19:07 | Filed under: Information Technology

McGill UniversityAssignments

  • Independence, conditionnal independence and Bayes network : [ Homework , Assignment ]
  • Bayes ball, variable elimination and junction tree algorithms, undirected and directed models, clique trees and I-Maps : [ Homework , Assignment ]
  • Likelihood weighting, Markov chain, Gibbs sampling, parameter estimation in Bayes nets, maximum likelihood estimation and learning Bayes net structure : [ Homework , Assignment ]
  • Expectation Maximization (EM), Hidden Markov Models (HMM) : [ Homework , Assignment ]
  • Expected Utility, Markov Decision Problem, Optimal policies, Action-values, Reinforcement learning, Exploration: [ Homework , Assignment ]

Programming Assignments : Junction Tree Algorithm and Approximate Inference methods

(Likelihood weighting and Gibbs sampling)

  • Group : Jérémie Juban
  • Subject : [ PDF ]

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