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» On regularization algorithms in learning theory
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KDD
2007
ACM
132views Data Mining» more  KDD 2007»
14 years 5 months ago
A scalable modular convex solver for regularized risk minimization
A wide variety of machine learning problems can be described as minimizing a regularized risk functional, with different algorithms using different notions of risk and different r...
Choon Hui Teo, Alex J. Smola, S. V. N. Vishwanatha...
NIPS
2000
13 years 6 months ago
Regularized Winnow Methods
In theory, the Winnow multiplicative update has certain advantages over the Perceptron additive update when there are many irrelevant attributes. Recently, there has been much eff...
Tong Zhang
ICML
2006
IEEE
14 years 6 months ago
A DC-programming algorithm for kernel selection
We address the problem of learning a kernel for a given supervised learning task. Our approach consists in searching within the convex hull of a prescribed set of basic kernels fo...
Andreas Argyriou, Raphael Hauser, Charles A. Micch...
ACL
2001
13 years 6 months ago
Text Chunking using Regularized Winnow
Many machine learning methods have recently been applied to natural language processing tasks. Among them, the Winnow algorithm has been argued to be particularly suitable for NLP...
Tong Zhang, Fred Damerau, David Johnson