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AROBOTS
2002
115views more  AROBOTS 2002»
15 years 3 months ago
Statistical Learning for Humanoid Robots
The complexity of the kinematic and dynamic structure of humanoid robots make conventional analytical approaches to control increasingly unsuitable for such systems. Learning techn...
Sethu Vijayakumar, Aaron D'Souza, Tomohiro Shibata...
SODA
2001
ACM
79views Algorithms» more  SODA 2001»
15 years 5 months ago
Learning Markov networks: maximum bounded tree-width graphs
Markov networks are a common class of graphical models used in machine learning. Such models use an undirected graph to capture dependency information among random variables in a ...
David R. Karger, Nathan Srebro
PKDD
2010
Springer
179views Data Mining» more  PKDD 2010»
15 years 1 months ago
Gaussian Processes for Sample Efficient Reinforcement Learning with RMAX-Like Exploration
Abstract. We present an implementation of model-based online reinforcement learning (RL) for continuous domains with deterministic transitions that is specifically designed to achi...
Tobias Jung, Peter Stone
IEEECIT
2010
IEEE
15 years 2 months ago
Application of Concept Maps-based Anchored Instruction in Programming Course
—In need of interesting material and effective teaching approach in programming learning, students were ely to drop out of the course for the abstract concepts and complex struct...
Liu Li, Haijun Mao, Licheng Xu
ICML
2006
IEEE
16 years 4 months ago
Maximum margin planning
Mobile robots often rely upon systems that render sensor data and perceptual features into costs that can be used in a planner. The behavior that a designer wishes the planner to ...
Nathan D. Ratliff, J. Andrew Bagnell, Martin Zinke...