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» Bayesian Gaussian Process Latent Variable Model
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121
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ICML
2009
IEEE
16 years 3 months ago
GAODE and HAODE: two proposals based on AODE to deal with continuous variables
AODE (Aggregating One-Dependence Estimators) is considered one of the most interesting representatives of the Bayesian classifiers, taking into account not only the low error rate...
Ana M. Martínez, José A. Gáme...
145
Voted
JMLR
2010
143views more  JMLR 2010»
14 years 9 months ago
Incremental Sigmoid Belief Networks for Grammar Learning
We propose a class of Bayesian networks appropriate for structured prediction problems where the Bayesian network's model structure is a function of the predicted output stru...
James Henderson, Ivan Titov
123
Voted
ICML
2004
IEEE
16 years 3 months ago
Parameter space exploration with Gaussian process trees
Computer experiments often require dense sweeps over input parameters to obtain a qualitative understanding of their response. Such sweeps can be prohibitively expensive, and are ...
Robert B. Gramacy, Herbert K. H. Lee, William G. M...
144
Voted
ICASSP
2009
IEEE
15 years 9 days ago
Probabilistic matrix tri-factorization
Nonnegative matrix tri-factorization (NMTF) is a 3-factor decomposition of a nonnegative data matrix, X USV , where factor matrices, U, S, and V , are restricted to be nonnegativ...
Jiho Yoo, Seungjin Choi
139
Voted
UAI
2000
15 years 3 months ago
Utilities as Random Variables: Density Estimation and Structure Discovery
Decision theory does not traditionally include uncertainty over utility functions. We argue that the a person's utility value for a given outcome can be treated as we treat o...
Urszula Chajewska, Daphne Koller