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CVPR
2007
IEEE
16 years 1 months ago
Variational Bayes Based Approach to Robust Subspace Learning
This paper presents a new algorithm for the problem of robust subspace learning (RSL), i.e., the estimation of linear subspace parameters from a set of data points in the presence...
Takayuki Okatani, Koichiro Deguchi
CVPR
2011
IEEE
14 years 7 months ago
Distributed Computer Vision Algorithms Through Distributed Averaging
Traditional computer vision and machine learning algorithms have been largely studied in a centralized setting, where all the processing is performed at a single central location....
Roberto Tron, René, Vidal
JMLR
2007
104views more  JMLR 2007»
14 years 11 months ago
Learnability of Gaussians with Flexible Variances
Gaussian kernels with flexible variances provide a rich family of Mercer kernels for learning algorithms. We show that the union of the unit balls of reproducing kernel Hilbert s...
Yiming Ying, Ding-Xuan Zhou
GECCO
2006
Springer
177views Optimization» more  GECCO 2006»
15 years 2 months ago
Hyper-ellipsoidal conditions in XCS: rotation, linear approximation, and solution structure
The learning classifier system XCS is an iterative rulelearning system that evolves rule structures based on gradient-based prediction and rule quality estimates. Besides classifi...
Martin V. Butz, Pier Luca Lanzi, Stewart W. Wilson
ICML
2009
IEEE
15 years 12 months ago
Robust bounds for classification via selective sampling
We introduce a new algorithm for binary classification in the selective sampling protocol. Our algorithm uses Regularized Least Squares (RLS) as base classifier, and for this reas...
Nicolò Cesa-Bianchi, Claudio Gentile, Franc...