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ICML
2007
IEEE
16 years 1 months ago
On one method of non-diagonal regularization in sparse Bayesian learning
In the paper we propose a new type of regularization procedure for training sparse Bayesian methods for classification. Transforming Hessian matrix of log-likelihood function to d...
Dmitry Kropotov, Dmitry Vetrov
GIS
1992
ACM
15 years 4 months ago
Machine Induction of Geospatial Knowledge
Machine learning techniques such as tree induction have become accepted tools for developing generalisations of large data sets, typically for use with production rule systems in p...
Peter A. Whigham, Robert I. McKay, J. R. Davis
KDD
2002
ACM
160views Data Mining» more  KDD 2002»
16 years 1 months ago
Scaling multi-class support vector machines using inter-class confusion
Support vector machines (SVMs) excel at two-class discriminative learning problems. They often outperform generative classifiers, especially those that use inaccurate generative m...
Shantanu Godbole, Sunita Sarawagi, Soumen Chakraba...
AAAI
2008
15 years 2 months ago
Markov Blanket Feature Selection for Support Vector Machines
Based on Information Theory, optimal feature selection should be carried out by searching Markov blankets. In this paper, we formally analyze the current Markov blanket discovery ...
Jianqiang Shen, Lida Li, Weng-Keen Wong
104
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ICML
2005
IEEE
16 years 1 months ago
Building Sparse Large Margin Classifiers
This paper presents an approach to build Sparse Large Margin Classifiers (SLMC) by adding one more constraint to the standard Support Vector Machine (SVM) training problem. The ad...
Bernhard Schölkopf, Gökhan H. Bakir, Min...