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CSDA
2007
134views more  CSDA 2007»
13 years 8 months ago
Variational approximations in Bayesian model selection for finite mixture distributions
Variational methods for model comparison have become popular in the neural computing/machine learning literature. In this paper we explore their application to the Bayesian analys...
Clare A. McGrory, D. M. Titterington
ICCV
2001
IEEE
14 years 10 months ago
The Variable Bandwidth Mean Shift and Data-Driven Scale Selection
We present two solutions for the scale selection problem in computer vision. The rst one is completely nonparametric and is based on the the adaptive estimation of the normalized ...
Dorin Comaniciu, Visvanathan Ramesh, Peter Meer
BMCBI
2008
139views more  BMCBI 2008»
13 years 8 months ago
The C1C2: A framework for simultaneous model selection and assessment
Background: There has been recent concern regarding the inability of predictive modeling approaches to generalize to new data. Some of the problems can be attributed to improper m...
Martin Eklund, Ola Spjuth, Jarl E. S. Wikberg
CVPR
2000
IEEE
14 years 11 days ago
Adaptive Bayesian Recognition in Tracking Rigid Objects
We present a framework for tracking rigid objects based on an adaptive Bayesian recognition technique that incorporates dependencies between object features. At each frame we fin...
Yuri Boykov, Daniel P. Huttenlocher
WSC
2004
13 years 9 months ago
Adaptive Control Variates
Adaptive Monte Carlo methods are specialized Monte Carlo simulation techniques where the methods are adaptively tuned as the simulation progresses. The primary focus of such techn...
Sujin Kim, Shane G. Henderson