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» Generalization Improvement in Multi-Objective Learning
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KDD
2008
ACM
150views Data Mining» more  KDD 2008»
16 years 24 days ago
Hypergraph spectral learning for multi-label classification
A hypergraph is a generalization of the traditional graph in which the edges are arbitrary non-empty subsets of the vertex set. It has been applied successfully to capture highord...
Liang Sun, Shuiwang Ji, Jieping Ye
ECML
2004
Springer
15 years 5 months ago
Batch Reinforcement Learning with State Importance
Abstract. We investigate the problem of using function approximation in reinforcement learning where the agent’s policy is represented as a classifier mapping states to actions....
Lihong Li, Vadim Bulitko, Russell Greiner
100
Voted
CEC
2010
IEEE
15 years 1 months ago
Generating a novel sort algorithm using Reinforcement Programming
Abstract-- Reinforcement Programming (RP) is a new approach to automatically generating algorithms, that uses reinforcement learning techniques. This paper describes the RP approac...
Spencer K. White, Tony R. Martinez, George L. Rudo...
IEICET
2007
94views more  IEICET 2007»
15 years 9 days ago
A New Meta-Criterion for Regularized Subspace Information Criterion
In order to obtain better generalization performance in supervised learning, model parameters should be determined appropriately, i.e., they should be determined so that the gener...
Yasushi Hidaka, Masashi Sugiyama
98
Voted
GECCO
2006
Springer
177views Optimization» more  GECCO 2006»
15 years 4 months ago
Hyper-ellipsoidal conditions in XCS: rotation, linear approximation, and solution structure
The learning classifier system XCS is an iterative rulelearning system that evolves rule structures based on gradient-based prediction and rule quality estimates. Besides classifi...
Martin V. Butz, Pier Luca Lanzi, Stewart W. Wilson