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PLDI
2011
ACM
13 years 23 days ago
EnerJ: approximate data types for safe and general low-power computation
Energy is increasingly a first-order concern in computer systems. Exploiting energy-accuracy trade-offs is an attractive choice in applications that can tolerate inaccuracies. Re...
Adrian Sampson, Werner Dietl, Emily Fortuna, Danus...
ATAL
2007
Springer
14 years 4 months ago
Model-based function approximation in reinforcement learning
Reinforcement learning promises a generic method for adapting agents to arbitrary tasks in arbitrary stochastic environments, but applying it to new real-world problems remains di...
Nicholas K. Jong, Peter Stone
IMA
2007
Springer
97views Cryptology» more  IMA 2007»
14 years 4 months ago
Non-linear Cryptanalysis Revisited: Heuristic Search for Approximations to S-Boxes
Non-linear cryptanalysis is a natural extension to Matsui’s linear cryptanalitic techniques in which linear approximations are replaced by nonlinear expressions. Non-linear appro...
Juan M. Estévez-Tapiador, John A. Clark, Ju...
SIGMOD
2008
ACM
142views Database» more  SIGMOD 2008»
14 years 10 months ago
Cost-based variable-length-gram selection for string collections to support approximate queries efficiently
Approximate queries on a collection of strings are important in many applications such as record linkage, spell checking, and Web search, where inconsistencies and errors exist in...
Xiaochun Yang, Bin Wang, Chen Li
ATAL
2005
Springer
14 years 3 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