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NIPS
2003
15 years 5 months ago
Probabilistic Inference in Human Sensorimotor Processing
When we learn a new motor skill, we have to contend with both the variability inherent in our sensors and the task. The sensory uncertainty can be reduced by using information abo...
Konrad P. Körding, Daniel M. Wolpert
FLAIRS
2000
15 years 5 months ago
Independence Semantics for BKBs
Bayesian KnowledgeBases (BKB)are a rule-based probabilistic modelthat extend BayesNetworks(BN), by allowing context-sensitive independenceand cycles in the directed graph. BKBshav...
Solomon Eyal Shimony, Eugene Santos Jr., Tzachi Ro...
CORR
2010
Springer
69views Education» more  CORR 2010»
15 years 4 months ago
A Geometric View of Conjugate Priors
In Bayesian machine learning, conjugate priors are popular, mostly due to mathematical convenience. In this paper, we show that there are deeper reasons for choosing a conjugate pr...
Arvind Agarwal, Hal Daumé III
JMLR
2011
167views more  JMLR 2011»
14 years 11 months ago
Logistic Stick-Breaking Process
A logistic stick-breaking process (LSBP) is proposed for non-parametric clustering of general spatially- or temporally-dependent data, imposing the belief that proximate data are ...
Lu Ren, Lan Du, Lawrence Carin, David B. Dunson
JMLR
2010
156views more  JMLR 2010»
14 years 10 months ago
Classification with Incomplete Data Using Dirichlet Process Priors
A non-parametric hierarchical Bayesian framework is developed for designing a classifier, based on a mixture of simple (linear) classifiers. Each simple classifier is termed a loc...
Chunping Wang, Xuejun Liao, Lawrence Carin, David ...