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» Evaluating learning algorithms and classifiers
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ICML
2009
IEEE
15 years 2 months ago
Multiple indefinite kernel learning with mixed norm regularization
We address the problem of learning classifiers using several kernel functions. On the contrary to many contributions in the field of learning from different sources of information...
Matthieu Kowalski, Marie Szafranski, Liva Ralaivol...
COLT
2008
Springer
15 years 6 months ago
An Efficient Reduction of Ranking to Classification
This paper describes an efficient reduction of the learning problem of ranking to binary classification. The reduction guarantees an average pairwise misranking regret of at most t...
Nir Ailon, Mehryar Mohri
ECIR
2003
Springer
15 years 6 months ago
Representative Sampling for Text Classification Using Support Vector Machines
In order to reduce human efforts, there has been increasing interest in applying active learning for training text classifiers. This paper describes a straightforward active learni...
Zhao Xu, Kai Yu, Volker Tresp, Xiaowei Xu, Jizhi W...
ECML
2006
Springer
15 years 8 months ago
Active Learning with Irrelevant Examples
Abstract. Active learning algorithms attempt to accelerate the learning process by requesting labels for the most informative items first. In real-world problems, however, there ma...
Dominic Mazzoni, Kiri Wagstaff, Michael C. Burl
JCC
2008
92views more  JCC 2008»
15 years 4 months ago
Two-electron integral evaluation on the graphics processor unit
: We propose the algorithm to evaluate the Coulomb potential in the ab initio density functional calculation on the graphics processor unit (GPU). The numerical accuracy required f...
Koji Yasuda