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chechetka's structure-learning [14 articles]

Recent papers added to chechetka's library classified by the tag structure-learning. You can also see everyone's structure-learning.
  • Causation, Prediction, and Search, Second Edition (Adaptive Computation and Machine Learning)
    (08 January 2001)
    by Peter Spirtes, Clark Glymour, Richard Scheines
  • Learning Bayesian Networks is NP-Complete
    (1996), pp. 121-130.
    by David M Chickering
    edited by D Fisher, HJ Lenz
  • Maximum Likelihood Bounded Tree-Width Markov Networks
    (2001), pp. 504-51.
    by Nathan Srebro
  • Inducing Features of Random Fields
    IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 19, No. 4. (April 1997), pp. 380-393.
    by Stephen Della Pietra, Vincent Della Pietra, John Lafferty
  • Finding Optimal Bayesian Networks by Dynamic Programming
    No. CMU-CALD-05-106. (2005)
    by Ajit Singh, Andrew Moore
  • Learning Factor Graphs in Polynomial Time and Sample Complexity
    Journal of Machine Learning Research, Vol. 7 (August 2006), pp. 1743-1788.
    by Pieter Abbeel, Daphne Koller, Andrew Y Ng
  • Ordering-based Search: A Simple and Effective Algorithm for Learning Bayesian Networks
    (2005)
    by Marc Teyssier, Daphne Koller
  • Approximating discrete probability distributions with dependence trees
    IEEE Transactions on Information Theory, Vol. 14, No. 3. (1968), pp. 462-467.
    by C Chow, C Liu
  • Learning with mixtures of trees
    Journal of Machine Learning Research, Vol. 1 (2001), pp. 1-48.
    by Marina Meil\ua, Michael I Jordan
    posted to _cited-by-nips2007 graphical-models structure-learning by chechetka on 2007-04-29 19:58:53 as read
  • On Bayesian Network Approximation by Edge Deletion
    (2005)
    by Arthur Choi, Hei Chan, Adnan Darwiche
  • Thin Junction Trees
    (2002)
    by Francis R Bach, Michael I Jordan
  • Being Bayesian About Network Structure. A Bayesian Approach to Structure Discovery in Bayesian Networks
    Machine Learning Journal, Vol. V50, No. 1. (1 January 2003), pp. 95-125.
    by Nir Friedman, Daphne Koller
  • Learning Graphical Models Over Partial k-Trees
    No. UWEETR-2004-0009. (2004)
    by Mukund Narasimhan, Jeff Bilmes
  • PAC-learning bounded tree-width graphical models
    (2004), pp. 410-417.
    by Mukund Narasimhan, Jeff Bilmes
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