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COLT
2007
Springer
16 years 19 days ago
Learning Large-Alphabet and Analog Circuits with Value Injection Queries
Abstract. We consider the problem of learning an acyclic discrete circuit with n wires, fan-in bounded by k and alphabet size s using value injection queries. For the class of tran...
Dana Angluin, James Aspnes, Jiang Chen, Lev Reyzin
COLT
1992
Springer
15 years 10 months ago
On Learning Limiting Programs
Machine learning of limit programs (i.e., programs allowed finitely many mind changes about their legitimate outputs) for computable functions is studied. Learning of iterated lim...
John Case, Sanjay Jain, Arun Sharma
ECML
2006
Springer
15 years 10 months ago
Approximate Policy Iteration for Closed-Loop Learning of Visual Tasks
Abstract. Approximate Policy Iteration (API) is a reinforcement learning paradigm that is able to solve high-dimensional, continuous control problems. We propose to exploit API for...
Sébastien Jodogne, Cyril Briquet, Justus H....
AAIP
2009
15 years 7 months ago
Incremental Learning in Inductive Programming
Inductive programming systems characteristically exhibit an exponential explosion in search time as one increases the size of the programs to be generated. As a way of overcoming ...
Robert Henderson
GECCO
2010
Springer
153views Optimization» more  GECCO 2010»
15 years 9 months ago
Multi-task evolutionary shaping without pre-specified representations
Shaping functions can be used in multi-task reinforcement learning (RL) to incorporate knowledge from previously experienced tasks to speed up learning on a new task. So far, rese...
Matthijs Snel, Shimon Whiteson