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» Algorithm Selection using Reinforcement Learning
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NIPS
2004
15 years 3 months ago
Computing regularization paths for learning multiple kernels
The problem of learning a sparse conic combination of kernel functions or kernel matrices for classification or regression can be achieved via the regularization by a block 1-norm...
Francis R. Bach, Romain Thibaux, Michael I. Jordan
GECCO
2006
Springer
159views Optimization» more  GECCO 2006»
15 years 6 months ago
Smart crossover operator with multiple parents for a Pittsburgh learning classifier system
This paper proposes a new smart crossover operator for a Pittsburgh Learning Classifier System. This operator, unlike other recent LCS approaches of smart recombination, does not ...
Jaume Bacardit, Natalio Krasnogor
DAARC
2007
Springer
86views Algorithms» more  DAARC 2007»
15 years 8 months ago
Evaluating Hybrid Versus Data-Driven Coreference Resolution
Abstract. In this paper, we present a systematic evaluation of a hybrid approach of combined rule-based filtering and machine learning to Dutch coreference resolution. Through the...
Iris Hendrickx, Véronique Hoste, Walter Dae...
SIGIR
2008
ACM
15 years 2 months ago
A bayesian logistic regression model for active relevance feedback
Relevance feedback, which traditionally uses the terms in the relevant documents to enrich the user's initial query, is an effective method for improving retrieval performanc...
Zuobing Xu, Ram Akella
ICCV
2005
IEEE
15 years 8 months ago
Image Based Regression Using Boosting Method
We present a general algorithm of image based regression that is applicable to many vision problems. The proposed regressor that targets a multiple-output setting is learned using...
Shaohua Kevin Zhou, Bogdan Georgescu, Xiang Sean Z...