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PKDD
2009
Springer
184views Data Mining» more  PKDD 2009»
15 years 11 months ago
Boosting Active Learning to Optimality: A Tractable Monte-Carlo, Billiard-Based Algorithm
Abstract. This paper focuses on Active Learning with a limited number of queries; in application domains such as Numerical Engineering, the size of the training set might be limite...
Philippe Rolet, Michèle Sebag, Olivier Teyt...
IJCAI
1989
15 years 7 months ago
Generation, Local Receptive Fields and Global Convergence Improve Perceptual Learning in Connectionist Networks
This paper presents and compares results for three types of connectionist networks on perceptual learning tasks: [A] Multi-layered converging networks of neuron-like units, with e...
Vasant Honavar, Leonard Uhr
GECCO
2008
Springer
126views Optimization» more  GECCO 2008»
15 years 7 months ago
Swarm intelligence in e-learning: a learning object sequencing agent based on competencies
In e-learning initiatives content creators are usually required to arrange a set of learning resources in order to present them in a comprehensive way to the learner. Course mater...
Luis de Marcos, José-Javier Martínez...
AIPS
2010
15 years 6 months ago
Iterative Learning of Weighted Rule Sets for Greedy Search
Greedy search is commonly used in an attempt to generate solutions quickly at the expense of completeness and optimality. In this work, we consider learning sets of weighted actio...
Yuehua Xu, Alan Fern, Sung Wook Yoon
AI
2008
Springer
15 years 6 months ago
Label ranking by learning pairwise preferences
Preference learning is a challenging problem that involves the prediction of complex structures, such as weak or partial order relations, rather than single values. In the recent ...
Eyke Hüllermeier, Johannes Fürnkranz, We...