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» Evaluating learning algorithms and classifiers
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ICML
1996
IEEE
14 years 11 months ago
Learning Relational Concepts with Decision Trees
In this paper, we describe two di erent learning tasks for relational structures. When learning a classi er for structures, the relational structures in the training sets are clas...
Peter Geibel, Fritz Wysotzki
ICML
2010
IEEE
13 years 11 months ago
Bayesian Multi-Task Reinforcement Learning
We consider the problem of multi-task reinforcement learning where the learner is provided with a set of tasks, for which only a small number of samples can be generated for any g...
Alessandro Lazaric, Mohammad Ghavamzadeh
SIGIR
2008
ACM
13 years 10 months ago
Personalized active learning for collaborative filtering
Collaborative Filtering (CF) requires user-rated training examples for statistical inference about the preferences of new users. Active learning strategies identify the most infor...
Abhay Harpale, Yiming Yang
EMO
2009
Springer
159views Optimization» more  EMO 2009»
14 years 5 months ago
Recombination for Learning Strategy Parameters in the MO-CMA-ES
The multi-objective covariance matrix adaptation evolution strategy (MO-CMA-ES) is a variable-metric algorithm for real-valued vector optimization. It maintains a parent population...
Thomas Voß, Nikolaus Hansen, Christian Igel
CIVR
2006
Springer
143views Image Analysis» more  CIVR 2006»
14 years 2 months ago
Asymmetric Learning and Dissimilarity Spaces for Content-Based Retrieval
Abstract. This paper presents novel dissimilarity space specially designed for interactive multimedia retrieval. By providing queries made of positive and negative examples, the go...
Eric Bruno, Nicolas Moënne-Loccoz, Sté...