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JMLR
2006
156views more  JMLR 2006»
15 years 4 months ago
Large Scale Multiple Kernel Learning
While classical kernel-based learning algorithms are based on a single kernel, in practice it is often desirable to use multiple kernels. Lanckriet et al. (2004) considered conic ...
Sören Sonnenburg, Gunnar Rätsch, Christi...
PAMI
2011
14 years 11 months ago
Multiple Kernel Learning for Dimensionality Reduction
—In solving complex visual learning tasks, adopting multiple descriptors to more precisely characterize the data has been a feasible way for improving performance. The resulting ...
Yen-Yu Lin, Tyng-Luh Liu, Chiou-Shann Fuh
CORR
2006
Springer
178views Education» more  CORR 2006»
15 years 4 months ago
Low-rank matrix factorization with attributes
We develop a new collaborative filtering (CF) method that combines both previously known users' preferences, i.e. standard CF, as well as product/user attributes, i.e. classi...
Jacob Abernethy, Francis Bach, Theodoros Evgeniou,...
ESANN
2007
15 years 5 months ago
How to process uncertainty in machine learning?
Uncertainty is a popular phenomenon in machine learning and a variety of methods to model uncertainty at different levels has been developed. The aim of this paper is to motivate ...
Barbara Hammer, Thomas Villmann
142
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AAMAS
2002
Springer
15 years 3 months ago
Multiagent Learning for Open Systems: A Study in Opponent Classification
Abstract. Open systems are becoming increasingly important in a variety of distributed, networked computer applications. Their characteristics, such as agent diversity, heterogenei...
Michael Rovatsos, Gerhard Weiß, Marco Wolf