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TNN
2010
148views Management» more  TNN 2010»
14 years 4 months ago
Generalized low-rank approximations of matrices revisited
Compared to Singular Value Decomposition (SVD), Generalized Low Rank Approximations of Matrices (GLRAM) can consume less computation time, obtain higher compression ratio, and yiel...
Jun Liu, Songcan Chen, Zhi-Hua Zhou, Xiaoyang Tan
76
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ESOP
2012
Springer
13 years 5 months ago
The Call-by-Need Lambda Calculus, Revisited
The existing call-by-need λ calculi describe lazy evaluation via equational logics. A programmer can use these logics to safely ascertain whether one term is behaviorally equivale...
Stephen Chang, Matthias Felleisen
IMA
2007
Springer
97views Cryptology» more  IMA 2007»
15 years 3 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...
AAAI
2006
14 years 11 months ago
Sample-Efficient Evolutionary Function Approximation for Reinforcement Learning
Reinforcement learning problems are commonly tackled with temporal difference methods, which attempt to estimate the agent's optimal value function. In most real-world proble...
Shimon Whiteson, Peter Stone
CEC
2011
IEEE
13 years 9 months ago
Stochastic Natural Gradient Descent by estimation of empirical covariances
—Stochastic relaxation aims at finding the minimum of a fitness function by identifying a proper sequence of distributions, in a given model, that minimize the expected value o...
Luigi Malagò, Matteo Matteucci, Giovanni Pi...