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» On Learning Boolean Functions
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DAC
2006
ACM
15 years 11 months ago
Topology aware mapping of logic functions onto nanowire-based crossbar architectures
Highly regular, nanodevice based architectures have been proposed to replace pure CMOS based architectures in the emerging post CMOS era. Since bottom-up self-assembly is used to ...
Wenjing Rao, Alex Orailoglu, Ramesh Karri
COCO
2010
Springer
144views Algorithms» more  COCO 2010»
15 years 1 months ago
A Regularity Lemma, and Low-Weight Approximators, for Low-Degree Polynomial Threshold Functions
We give a “regularity lemma” for degree-d polynomial threshold functions (PTFs) over the Boolean cube {−1, 1}n . Roughly speaking, this result shows that every degree-d PTF ...
Ilias Diakonikolas, Rocco A. Servedio, Li-Yang Tan...
GECCO
2008
Springer
120views Optimization» more  GECCO 2008»
14 years 11 months ago
Genetic programming with polymorphic types and higher-order functions
This article introduces our new approach to program representation for genetic programming (GP). We replace the usual s-expression representation scheme by a strongly-typed ion-ba...
Franck Binard, Amy P. Felty
ATAL
2008
Springer
14 years 12 months ago
Transfer of task representation in reinforcement learning using policy-based proto-value functions
Reinforcement Learning research is traditionally devoted to solve single-task problems. Therefore, anytime a new task is faced, learning must be restarted from scratch. Recently, ...
Eliseo Ferrante, Alessandro Lazaric, Marcello Rest...
CIG
2005
IEEE
15 years 3 months ago
Adapting Reinforcement Learning for Computer Games: Using Group Utility Functions
AbstractGroup utility functions are an extension of the common team utility function for providing multiple agents with a common reinforcement learning signal for learning cooperat...
Jay Bradley, Gillian Hayes