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» Using Gaussian Processes to Optimize Expensive Functions
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ICCS
2003
Springer
14 years 28 days ago
A Method of Hidden Markov Model Optimization for Use with Geophysical Data Sets
Geophysics research has been faced with a growing need for automated techniques with which to process large quantities of data. A successful tool must meet a number of requirements...
Robert A. Granat
ICML
2005
IEEE
14 years 8 months ago
Active learning for Hidden Markov Models: objective functions and algorithms
Hidden Markov Models (HMMs) model sequential data in many fields such as text/speech processing and biosignal analysis. Active learning algorithms learn faster and/or better by cl...
Brigham Anderson, Andrew Moore
NIPS
2000
13 years 9 months ago
Occam's Razor
The Bayesian paradigm apparently only sometimes gives rise to Occam's Razor; at other times very large models perform well. We give simple examples of both kinds of behaviour...
Carl Edward Rasmussen, Zoubin Ghahramani
FGR
2000
IEEE
181views Biometrics» more  FGR 2000»
14 years 4 days ago
Face Detection Using Mixtures of Linear Subspaces
We present two methods using mixtures of linear subspaces for face detection in gray level images. One method uses a mixture of factor analyzers to concurrently perform clustering...
Ming-Hsuan Yang, Narendra Ahuja, David J. Kriegman
IJON
2007
88views more  IJON 2007»
13 years 7 months ago
Information maximization in face processing
This perspective paper explores principles of unsupervised learning and how they relate to face recognition. Dependency coding and information maximization appear to be central pr...
Marian Stewart Bartlett