Learning with Mixtures of Trees

Learning with Mixtures of Trees (1999)

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by Marina Meila-Predoviciu

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@MISC{Meila-Predoviciu99learningwith,
    author = {Marina Meila-Predoviciu},
    title = {Learning with Mixtures of Trees},
    year = {1999}
}

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7321	Introduction to Algorithms - Cormen, Leiserson, et al. - 2001
6514	Elements of Information Theory - Cover, Thomas - 1991
6231	Maximum likelihood from incomplete data via the EM algorithm - Dempster, Laird - 1977
5664	Probabilistic Reasoning in Intelligent Systems - Pearl - 1988
3011	Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images - Geman - 1984
877	A Bayesian method for the induction of probabilistic networks from data - Cooper, Herskovits - 1992
844	Graphical Models - Lauritzen - 1996
809	On information and sufficiency - Kullback, Leibler - 1951
752	Learning Bayesian networks: the combination of knowledge and statistical data - Heckerman, Geiger, et al. - 1995
719	FV: An Introduction to Bayesian Networks - Jensen - 1996
615	Introduction to Graph Theory - West - 2001
581	Low-Density Parity-Check Codes - Gallager - 1963
496	The computational complexity of probabilistic inference using Bayesian belief networks - Cooper - 1990
487	Approximating discrete probability distributions with dependence trees - Chow, Liu - 1968
451	Bayesian Network Classifiers - Friedman, Geiger, et al. - 1997
416	Bayesian classification (AutoClass): Theory and results - Cheeseman, Stutz - 1996
354	Graphical Models in Applied Multivariate Statistics - Whittaker - 2009
342	Near optimum error correcting coding and decoding: turbo codes - Berrou, Glavieux - 1996
258	Stochastic Complexity in Statistical Inquiry - Rissanen - 1989
248	A tutorial on learning Bayesian networks - Heckerman - 1995
240	Bayesian updating in causal probabilistic networks by local computations - Jensen, Lauritzen, et al. - 1990
213	Model selection and accounting for model uncertainty in graphical models using Occam’s window - Madigan, Raftery - 1994
205	Near Shannon limit performance of low-density parity check codes - MacKay, Neal - 1996
160	Connectionist learning of belief networks - Neal - 1992
149	On structuring probabilistic dependencies in stochastic language modeling. Computer Speech and Language - Ney, Essen, et al. - 1994
83	Slink: an optimally efficient algorithm for the single-link cluster method - SIBSON - 1973
81	Knowledge representation and inference in similarity networks and bayesian multinets - Geiger, Heckerman - 1996
76	Applications of a general propagation algorithm for probabilistic expert systems - Dawid - 1992
72	M.: Building classifiers using bayesian networks. In - Friedman, Goldszmidt - 1996
66	Training knowledge-based neural networks to recognize genes in dna sequences - Noordewieer, Towell, et al. - 1991
64	Belief propagation and revision in networks with loops - Weiss - 1997
63	Optimal junction trees - Jensen, Jensen - 1994
62	A sufficiently fast algorithm for finding close to optimal clique trees - Becker, Geiger
55	An algorithm for deciding if a set of observed independencies has a causal explanation - Verma, Pearl - 1992
52	Competition and multiple cause models - Dayan, Zemel - 1995
52	Interpretation of artificial neural networks: Mapping knowledge-based neural networks into rules - Towell, Shavlik - 1992
48	Learning belief networks from data: An information theory based approach - Cheng, Bell, et al. - 1997
47	Variational Methods for Inference and Estimation in Graphical Models - Jaakkola - 1997
39	S.: Localized Partial Evaluation of Belief Networks - Draper, Hanks - 1995
38	Endre Tarjan. Data structures and network algorithms - Robert - 1983
37	On information and suciency - Kullback, Leibler - 1951
31	Learning polytrees - Dasgupta - 1999
28	An entropy-based learning algorithm of Bayesian conditional trees - Geiger
27	Fredman and Robert Endre Tarjan. Fibonacci heaps and their uses in improved network optimization algorithms - Michael - 1987
25	Estimating dependency structure as a hidden variable - Meila, Jordan - 1998
23	Bayesian network classification with continuous attributes: Getting the best of both discretization and parametric fitting - Friedman, Goldszmidt, et al. - 1998
23	Spiegelhalter (Editors), ‘Markov Chain Monte Carlo in Practice’, Chapman and - See, Gilks, et al. - 1996
23	Nonlinear markov networks for continuous variables - Hofmann, Tresp - 1998
22	Does the wake-sleep algorithm produce good density estimators - Frey, Hinton, et al. - 1996
18	Constructing bayesian finite mixture models by the em algorithm - Kontkanen, Myllymäki, et al. - 1996