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» Semi-Naive Bayesian Classifier
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UAI
2001
13 years 9 months ago
Expectation Propagation for approximate Bayesian inference
This paper presents a new deterministic approximation technique in Bayesian networks. This method, "Expectation Propagation," unifies two previous techniques: assumed-de...
Thomas P. Minka
AVSS
2006
IEEE
13 years 11 months ago
Classification-Based Likelihood Functions for Bayesian Tracking
The success of any Bayesian particle filtering based tracker relies heavily on the ability of the likelihood function to discriminate between the state that fits the image well an...
Chunhua Shen, Hongdong Li, Michael J. Brooks
ICPR
2000
IEEE
14 years 8 months ago
Invariant Image Object Recognition Using Mixture Densities
In this paper we present a mixture density based approach to invariant image object recognition. We start our experiments using Gaussian mixture densities within a Bayesian classi...
Daniel Keysers, Hermann Ney, Jörg Dahmen, Mar...
ICML
2000
IEEE
14 years 8 months ago
Solving the Multiple-Instance Problem: A Lazy Learning Approach
As opposed to traditional supervised learning, multiple-instance learning concerns the problem of classifying a bag of instances, given bags that are labeled by a teacher as being...
Jun Wang, Jean-Daniel Zucker
ICMCS
2006
IEEE
167views Multimedia» more  ICMCS 2006»
14 years 1 months ago
Automatic Classification of Field of View in Video
Automatic systems are needed for audiovisual databases to efficiently index, browse, summarize and retrieve, because the amount of stored data is increasing tremendously. Historic...
Maria Ferrer, Mauro Barbieri, Hans Weda