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John S. Breese, David Heckerman, Carl Myers Kadie : Empirical Analysis of Predictive Algorithms for Collaborative Filtering CoRR abs/1301.7363(): (2013)
John S. Breese, David Heckerman, Carl Myers Kadie : Empirical Analysis of Predictive Algorithms for Collaborative Filtering. UAI 1998
David Heckerman, Dan Geiger, David Maxwell Chickering : Learning Bayesian Networks: The Combination of Knowledge and Statistical Data CoRR abs/1302.6815(): (2013)
David Heckerman, Dan Geiger, David Maxwell Chickering : Learning Bayesian Networks: The Combination of Knowledge and Statistical Data. Machine Learning (ML) 20(3):197-243 (1995)
David Heckerman, Dan Geiger, David Maxwell Chickering : Learning Bayesian Networks: The Combination of Knowledge and Statistical Data. UAI 1994
David Heckerman, Dan Geiger, David Maxwell Chickering : Learning Bayesian Networks: The Combination of Knowledge and Statistical Data. KDD Workshop (KDD) 1994
Eric Horvitz, John S. Breese, David Heckerman, David Hovel, Koos Rommelse : The Lumiere Project: Bayesian User Modeling for Inferring the Goals and Needs of Software Users CoRR abs/1301.7385(): (2013)
David Maxwell Chickering, David Heckerman : Efficient Approximations for the Marginal Likelihood of Bayesian Networks with Hidden Variables. Machine Learning (ML) 29(2-3):181-212 (1997)
Padhraic Smyth, David Heckerman, Michael I. Jordan : Probabilistic Independence Networks for Hidden Markov Probability Models. Neural Computation (NECO) 9(2):227-269 (1997)
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