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ECML
2006
Springer
14 years 15 days ago
Bayesian Active Learning for Sensitivity Analysis
Abstract. Designs of micro electro-mechanical devices need to be robust against fluctuations in mass production. Computer experiments with tens of parameters are used to explore th...
Tobias Pfingsten
EDUTAINMENT
2007
Springer
14 years 3 months ago
Method of Motion Data Processing Based on Manifold Learning
Due to the high-dimensionality of motion captured data which resulted in the complexity in motion analysis, a method of motion data processing based on manifold learning was propos...
Fengxia Li, Tianyu Huang, Lijie Li
ICML
2009
IEEE
14 years 9 months ago
Constraint relaxation in approximate linear programs
Approximate Linear Programming (ALP) is a reinforcement learning technique with nice theoretical properties, but it often performs poorly in practice. We identify some reasons for...
Marek Petrik, Shlomo Zilberstein
COLT
2000
Springer
14 years 1 months ago
Computable Shell Decomposition Bounds
Haussler, Kearns, Seung and Tishby introduced the notion of a shell decomposition of the union bound as a means of understanding certain empirical phenomena in learning curves suc...
John Langford, David A. McAllester
ICML
2010
IEEE
13 years 10 months ago
Internal Rewards Mitigate Agent Boundedness
Abstract--Reinforcement learning (RL) research typically develops algorithms for helping an RL agent best achieve its goals-however they came to be defined--while ignoring the rela...
Jonathan Sorg, Satinder P. Singh, Richard Lewis