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» Graph model selection using maximum likelihood
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ICDM
2008
IEEE
107views Data Mining» more  ICDM 2008»
14 years 3 months ago
Graph-Based Iterative Hybrid Feature Selection
When the number of labeled examples is limited, traditional supervised feature selection techniques often fail due to sample selection bias or unrepresentative sample problem. To ...
ErHeng Zhong, Sihong Xie, Wei Fan, Jiangtao Ren, J...
SSPR
2004
Springer
14 years 2 months ago
An Optimal Probabilistic Graphical Model for Point Set Matching
We present a probabilistic graphical model for point set matching. By using a result about the redundancy of the pairwise distances in a point set, we represent the binary relation...
Tibério S. Caetano, Terry Caelli, Dante Aug...
CDC
2009
IEEE
186views Control Systems» more  CDC 2009»
14 years 26 days ago
Distributed function and time delay estimation using nonparametric techniques
In this paper we analyze the problem of estimating a function from different noisy data sets collected by spatially distributed sensors and subject to unknown temporal shifts. We p...
Damiano Varagnolo, Gianluigi Pillonetto, Luca Sche...
JMLR
2011
148views more  JMLR 2011»
13 years 3 months ago
Multitask Sparsity via Maximum Entropy Discrimination
A multitask learning framework is developed for discriminative classification and regression where multiple large-margin linear classifiers are estimated for different predictio...
Tony Jebara
MIR
2006
ACM
223views Multimedia» more  MIR 2006»
14 years 2 months ago
Adaptive image retrieval using a Graph model for semantic feature integration
The variety of features available to represent multimedia data constitutes a rich pool of information. However, the plethora of data poses a challenge in terms of feature selectio...
Jana Urban, Joemon M. Jose