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ICMLA
2010
14 years 11 months ago
Incremental Learning of Relational Action Rules
Abstract--In the Relational Reinforcement learning framework, we propose an algorithm that learns an action model allowing to predict the resulting state of each action in any give...
Christophe Rodrigues, Pierre Gérard, C&eacu...
ICMLA
2010
15 years 8 days ago
Smoothing Gene Expression Using Biological Networks
Gene expression (microarray) data have been used widely in bioinformatics. The expression data of a large number of genes from small numbers of subjects are used to identify inform...
Yue Fan, Mark A. Kon, Shinuk Kim, Charles DeLisi
ICML
2003
IEEE
16 years 3 months ago
Learning Metrics via Discriminant Kernels and Multidimensional Scaling: Toward Expected Euclidean Representation
Distance-based methods in machine learning and pattern recognition have to rely on a metric distance between points in the input space. Instead of specifying a metric a priori, we...
Zhihua Zhang
120
Voted
MM
2010
ACM
137views Multimedia» more  MM 2010»
15 years 2 months ago
Self-diagnostic peer-assisted video streaming through a learning framework
Quality control and resource optimization are challenging problems in peer-assisted video streaming systems, due to their large scales and unreliable peer behavior. Such systems a...
Di Niu, Baochun Li, Shuqiao Zhao
GECCO
2006
Springer
138views Optimization» more  GECCO 2006»
15 years 6 months ago
Does overfitting affect performance in estimation of distribution algorithms
Estimation of Distribution Algorithms (EDAs) are a class of evolutionary algorithms that use machine learning techniques to solve optimization problems. Machine learning is used t...
Hao Wu, Jonathan L. Shapiro