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    IJCAI
    2007
    254views Artificial Intelligence» more  IJCAI 2007»
    Bayesian Inverse Reinforcement Learning
    15 years 5 months ago
    Bayesian Inverse Reinforcement Learning
    Download  www.ijcai.org
    Inverse Reinforcement Learning (IRL) is the problem of learning the reward function underlying a Markov Decision Process given the dynamics of the system and the behaviour of an e...
    Deepak Ramachandran, Eyal Amir
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    KDD
    1994
    ACM
    123views Data Mining» more  KDD 1994»
    Learning Bayesian Networks: The Combination of Knowledge and Statistical Data
    15 years 8 months ago
    Learning Bayesian Networks: The Combination of Knowledge and Statistical Data
    Download  research.microsoft.com
    We describe scoring metrics for learning Bayesian networks from a combination of user knowledge and statistical data. We identify two important properties of metrics, which we cal...
    David Heckerman, Dan Geiger, David Maxwell Chicker...
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    ICML
    2006
    IEEE
    137views Machine Learning» more  ICML 2006»
    Bayesian multi-population haplotype inference via a hierarchical dirichlet process mixture
    16 years 4 months ago
    Bayesian multi-population haplotype inference via a hierarchical dirichlet process mixture
    Download  www.gatsby.ucl.ac.uk
    Eric P. Xing, Kyung-Ah Sohn, Michael I. Jordan, Ye...
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    ICML
    2003
    IEEE
    148views Machine Learning» more  ICML 2003»
    Bayesian Network Anomaly Pattern Detection for Disease Outbreaks
    16 years 4 months ago
    Bayesian Network Anomaly Pattern Detection for Disease Outbreaks
    Download  www.aaai.org
    Weng-Keen Wong, Andrew W. Moore, Gregory F. Cooper...
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    NIPS
    2004
    145views Information Technology» more  NIPS 2004»
    Learning Gaussian Process Kernels via Hierarchical Bayes
    15 years 5 months ago
    Learning Gaussian Process Kernels via Hierarchical Bayes
    Download  books.nips.cc
    We present a novel method for learning with Gaussian process regression in a hierarchical Bayesian framework. In a first step, kernel matrices on a fixed set of input points are l...
    Anton Schwaighofer, Volker Tresp, Kai Yu
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