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UAI
2008
15 years 4 months ago
Model-Based Bayesian Reinforcement Learning in Large Structured Domains
Model-based Bayesian reinforcement learning has generated significant interest in the AI community as it provides an elegant solution to the optimal exploration-exploitation trade...
Stéphane Ross, Joelle Pineau
100
Voted
ICPR
2006
IEEE
16 years 3 months ago
A New Data Selection Principle for Semi-Supervised Incremental Learning
Current semi-supervised incremental learning approaches select unlabeled examples with predicted high confidence for model re-training. We show that for many applications this dat...
Alexander I. Rudnicky, Rong Zhang
118
Voted
PKDD
2007
Springer
193views Data Mining» more  PKDD 2007»
15 years 8 months ago
Learning Multi-dimensional Functions: Gas Turbine Engine Modeling
Abstract. This paper shows how multi-dimensional functions, describing the operation of complex equipment, can be learned. The functions are points in a shape space, each produced ...
Chris Drummond
ESWS
2008
Springer
15 years 4 months ago
Learning Highly Structured Semantic Repositories from Relational Databases:
Abstract. Relational databases are valuable sources for ontology learning. Methods and tools have been proposed to generate ontologies from such structured input. However, a major ...
Farid Cerbah
ICRA
1999
IEEE
122views Robotics» more  ICRA 1999»
15 years 6 months ago
Learning Visual Landmarks for Pose Estimation
Abstract-- We present an approach to vision-based mobile robot localization, even without an a-priori pose estimate. This is accomplished by learning a set of visual features calle...
Robert Sim, Gregory Dudek