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IJCNN
2006
IEEE
16 years 19 days ago
Alleviating Catastrophic Forgetting via Multi-Objective Learning
— Handling catastrophic forgetting is an interesting and challenging topic in modeling the memory mechanisms of the human brain using machine learning models. From a more general...
Yaochu Jin, Bernhard Sendhoff
COLT
1998
Springer
15 years 10 months ago
Self Bounding Learning Algorithms
Most of the work which attempts to give bounds on the generalization error of the hypothesis generated by a learning algorithm is based on methods from the theory of uniform conve...
Yoav Freund
195
Voted
EWRL
2008
15 years 8 months ago
Policy Learning - A Unified Perspective with Applications in Robotics
Policy Learning approaches are among the best suited methods for high-dimensional, continuous control systems such as anthropomorphic robot arms and humanoid robots. In this paper,...
Jan Peters, Jens Kober, Duy Nguyen-Tuong
IJCAI
2007
15 years 8 months ago
Bayesian Inverse Reinforcement Learning
Inverse Reinforcement Learning (IRL) is the problem of learning the reward function underlying a Markov Decision Process given the dynamics of the system and the behaviour of an e...
Deepak Ramachandran, Eyal Amir
FLAIRS
2001
15 years 8 months ago
User-Agent Interactions in Mixed-Initiative Learning
Mixed-initiative learning integrates complementary human and automated reasoning, taking advantage of their respective reasoning styles and computational strengths in order to sol...
Dorin Marcu, Mihai Boicu, Gheorghe Tecuci