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ICIP
1999
IEEE
14 years 9 months ago
Uncertainties in Bayesian Geometric Models
Deformable geometric models fit very naturally into the context of Bayesian analysis. The prior probability of boundary shapes is taken to proportional to the negative exponential...
Kenneth M. Hanson, Gregory S. Cunningham, Robert J...
ICPR
2000
IEEE
14 years 9 months ago
Statistical Motion-Based Object Indexing Using Optic Flow Field
In this paper, we propose an original approach for content-based video indexing and retrieval. It relies on the tracking of entities of interest and the analysis of their apparent...
Ronan Fablet, Patrick Bouthemy
ICML
2009
IEEE
14 years 9 months ago
Model-free reinforcement learning as mixture learning
We cast model-free reinforcement learning as the problem of maximizing the likelihood of a probabilistic mixture model via sampling, addressing both the infinite and finite horizo...
Nikos Vlassis, Marc Toussaint
ICML
2007
IEEE
14 years 9 months ago
Dimensionality reduction and generalization
In this paper we investigate the regularization property of Kernel Principal Component Analysis (KPCA), by studying its application as a preprocessing step to supervised learning ...
Sofia Mosci, Lorenzo Rosasco, Alessandro Verri
ICML
2006
IEEE
14 years 9 months ago
Hidden process models
We introduce Hidden Process Models (HPMs), a class of probabilistic models for multivariate time series data. The design of HPMs has been motivated by the challenges of modeling h...
Rebecca Hutchinson, Tom M. Mitchell, Indrayana Rus...