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IDA
2002
Springer
15 years 6 months ago
Evolutionary model selection in unsupervised learning
Feature subset selection is important not only for the insight gained from determining relevant modeling variables but also for the improved understandability, scalability, and pos...
YongSeog Kim, W. Nick Street, Filippo Menczer
CVPR
2004
IEEE
16 years 8 months ago
Learning a Restricted Bayesian Network for Object Detection
Many classes of images have the characteristics of sparse structuring of statistical dependency and the presence of conditional independencies among various groups of variables. S...
Henry Schneiderman
ECCV
2008
Springer
16 years 8 months ago
Efficiently Learning Random Fields for Stereo Vision with Sparse Message Passing
As richer models for stereo vision are constructed, there is a growing interest in learning model parameters. To estimate parameters in Markov Random Field (MRF) based stereo formu...
Jerod J. Weinman, Lam Tran, Christopher J. Pal
ECCV
2002
Springer
16 years 8 months ago
Learning the Topology of Object Views
A visual representation of an object must meet at least three basic requirements. First, it must allow identification of the object in the presence of slight but unpredictable chan...
Christoph von der Malsburg, Jan Wieghardt, Rolf P....
SDM
2009
SIAM
119views Data Mining» more  SDM 2009»
16 years 3 months ago
Twin Vector Machines for Online Learning on a Budget.
This paper proposes Twin Vector Machine (TVM), a constant space and sublinear time Support Vector Machine (SVM) algorithm for online learning. TVM achieves its favorable scaling b...
Zhuang Wang, Slobodan Vucetic