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ICCV
2007
IEEE
16 years 4 months ago
Learning Multiscale Representations of Natural Scenes Using Dirichlet Processes
We develop nonparametric Bayesian models for multiscale representations of images depicting natural scene categories. Individual features or wavelet coefficients are marginally de...
Jyri J. Kivinen, Erik B. Sudderth, Michael I. Jord...
139
Voted
ICML
2009
IEEE
16 years 3 months ago
Archipelago: nonparametric Bayesian semi-supervised learning
Semi-supervised learning (SSL), is classification where additional unlabeled data can be used to improve accuracy. Generative approaches are appealing in this situation, as a mode...
Ryan Prescott Adams, Zoubin Ghahramani
HICSS
2006
IEEE
114views Biometrics» more  HICSS 2006»
15 years 8 months ago
New Probabilistic Method for Estimation of Equipment Failures and Development of Replacement Strategies
When large amount of statistical information about power system component failure rate is available, statistical parametric models can be developed for predictive maintenance. Oft...
Miroslav Begovic, Petar M. Djuric, Joshua Perkel, ...
98
Voted
EMNLP
2007
15 years 4 months ago
A Probabilistic Approach to Diachronic Phonology
We present a probabilistic model of diachronic phonology in which individual word forms undergo stochastic edits along the branches of a phylogenetic tree. Our approach allows us ...
Alexandre Bouchard-Côté, Percy Liang,...
EOR
2006
113views more  EOR 2006»
15 years 2 months ago
Validation of regression metamodels in simulation: Bootstrap approach
Simulation experiments are often analyzed through a linear regression model of their input/output data. Such an analysis yields a metamodel or response surface for the underlying ...
Jack P. C. Kleijnen, David Deflandre