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FOCM
2008
140views more  FOCM 2008»
13 years 10 months ago
Online Gradient Descent Learning Algorithms
This paper considers the least-square online gradient descent algorithm in a reproducing kernel Hilbert space (RKHS) without explicit regularization. We present a novel capacity i...
Yiming Ying, Massimiliano Pontil
CVPR
2011
IEEE
13 years 7 months ago
Sparsity-based Image Denoising via Dictionary Learning and Structural Clustering
Where does the sparsity in image signals come from? Local and nonlocal image models have supplied complementary views toward the regularity in natural images the former attempts t...
Weisheng Dong, Xin Li
COGSR
2011
105views more  COGSR 2011»
13 years 4 months ago
Inductive rule learning on the knowledge level
We present an application of the analytical inductive programming system Igor to learning sets of recursive rules from positive experience. We propose that this approach can be us...
Ute Schmid, Emanuel Kitzelmann
ECML
2007
Springer
14 years 1 months ago
On Pairwise Naive Bayes Classifiers
Class binarizations are effective methods for improving weak learners by decomposing multi-class problems into several two-class problems. This paper analyzes how these methods can...
Jan-Nikolas Sulzmann, Johannes Fürnkranz, Eyk...
GECCO
2000
Springer
114views Optimization» more  GECCO 2000»
14 years 1 months ago
Intelligent Recombination Using Individual Learning in a Collective Learning Genetic Algorithm
This paper introduces a new collective learning genetic algorithm (CLGA) which employs individual learning to do intelligent recombination based on a cooperative exchange of knowl...
Terry P. Riopka, Peter Bock