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» Using a probabilistic source model for comparing images
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ICML
2004
IEEE
14 years 8 months ago
Improving SVM accuracy by training on auxiliary data sources
The standard model of supervised learning assumes that training and test data are drawn from the same underlying distribution. This paper explores an application in which a second...
Pengcheng Wu, Thomas G. Dietterich
ICIP
2008
IEEE
14 years 1 months ago
Incorporating known features into a total variation dictionary model for source separation
The goal of this paper is to investigate the impact of dictionary choosing for a total variation dictionary model. After theoretical analysis, we present the experiments in which ...
Tieyong Zeng
CCIA
2008
Springer
13 years 9 months ago
Probabilistic Dynamic Belief Logic for Image and Reputation
Since electronic and open environments became a reality, computational trust and reputation models have attracted increasing interest in the field of multiagent systems (MAS). Some...
Isaac Pinyol, Jordi Sabater-Mir, Pilar Dellunde
CVPR
2008
IEEE
14 years 9 months ago
Learning for stereo vision using the structured support vector machine
We present a random field based model for stereo vision with explicit occlusion labeling in a probabilistic framework. The model employs non-parametric cost functions that can be ...
Yunpeng Li, Daniel P. Huttenlocher
CVPR
2008
IEEE
14 years 9 months ago
Latent topic random fields: Learning using a taxonomy of labels
An important problem in image labeling concerns learning with images labeled at varying levels of specificity. We propose an approach that can incorporate images with labels drawn...
Xuming He, Richard S. Zemel