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ICML
1998
IEEE
14 years 9 months ago
Q2: Memory-Based Active Learning for Optimizing Noisy Continuous Functions
This paper introduces a new algorithm, Q2, foroptimizingthe expected output ofamultiinput noisy continuous function. Q2 is designed to need only a few experiments, it avoids stron...
Andrew W. Moore, Jeff G. Schneider, Justin A. Boya...
ATAL
2005
Springer
14 years 2 months ago
Improving reinforcement learning function approximators via neuroevolution
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
Shimon Whiteson
EH
1999
IEEE
351views Hardware» more  EH 1999»
14 years 26 days ago
Evolvable Hardware or Learning Hardware? Induction of State Machines from Temporal Logic Constraints
Here we advocate an approach to learning hardware based on induction of finite state machines from temporal logic constraints. The method involves training on examples, constraint...
Marek A. Perkowski, Alan Mishchenko, Anatoli N. Ch...
ICFP
2003
ACM
14 years 8 months ago
Functional automatic differentiation with dirac impulses
Functional Reactive Programming (FRP) is a framework for reactive programming in a functional setting. FRP has been applied to a number of domains, such as graphical animation, gr...
Henrik Nilsson
ESA
2007
Springer
176views Algorithms» more  ESA 2007»
14 years 2 months ago
Arrangements in Geometry: Recent Advances and Challenges
We review recent progress in the study of arrangements in computational and combinatorial geometry, and discuss several open problems and areas for further research. In this talk I...
Micha Sharir