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CORR
2008
Springer
142views Education» more  CORR 2008»
13 years 7 months ago
A Gaussian Belief Propagation Solver for Large Scale Support Vector Machines
Support vector machines (SVMs) are an extremely successful type of classification and regression algorithms. Building an SVM entails solving a constrained convex quadratic program...
Danny Bickson, Elad Yom-Tov, Danny Dolev
JMLR
2010
104views more  JMLR 2010»
13 years 2 months ago
Increasing Feature Selection Accuracy for L1 Regularized Linear Models
L1 (also referred to as the 1-norm or Lasso) penalty based formulations have been shown to be effective in problem domains when noisy features are present. However, the L1 penalty...
Abhishek Jaiantilal, Gregory Z. Grudic
KDD
2006
ACM
165views Data Mining» more  KDD 2006»
14 years 8 months ago
Training linear SVMs in linear time
Linear Support Vector Machines (SVMs) have become one of the most prominent machine learning techniques for highdimensional sparse data commonly encountered in applications like t...
Thorsten Joachims
TOG
2008
102views more  TOG 2008»
13 years 7 months ago
Real-time data driven deformation using kernel canonical correlation analysis
Achieving intuitive control of animated surface deformation while observing a specific style is an important but challenging task in computer graphics. Solutions to this task can ...
Wei-Wen Feng, Byung-Uck Kim, Yizhou Yu
SMI
2008
IEEE
127views Image Analysis» more  SMI 2008»
14 years 2 months ago
Optimal bandwidth selection for MLS surfaces
We address the problem of bandwidth selection in MLS surfaces. While the problem has received relatively little attention in the literature, we show that appropriate selection pla...
Hao Wang, Carlos Eduardo Scheidegger, Cláud...