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» Gradient estimation in global optimization algorithms
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UAI
2001
15 years 29 days ago
The Optimal Reward Baseline for Gradient-Based Reinforcement Learning
There exist a number of reinforcement learning algorithms which learn by climbing the gradient of expected reward. Their long-run convergence has been proved, even in partially ob...
Lex Weaver, Nigel Tao
SIP
2003
15 years 29 days ago
Time Domain Optimization Techniques for Blind Separation of Non-stationary Convolutive Mixed Signals
This paper aims to solve the problem of Blind Signal Separation (BSS) in a convolutive environment based on output correlation matrix diagonalization. Firstly an extension of the ...
Iain Russell, Alfred Mertins, Jiangtao Xi
CEC
2011
IEEE
13 years 11 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...
ICCD
2001
IEEE
154views Hardware» more  ICCD 2001»
15 years 8 months ago
Performance Optimization By Wire and Buffer Sizing Under The Transmission Line Model
As the operating frequency increases to Giga Hertz and the rise time of a signal is less than or comparable to the time-of-flight delay of a line, it is necessary to consider the...
Tai-Chen Chen, Song-Ra Pan, Yao-Wen Chang
90
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WSC
2001
15 years 29 days ago
Global random optimization by simultaneous perturbation stochastic approximation
We examine the theoretical and numerical global convergence properties of a certain "gradient free" stochastic approximation algorithm called the "simultaneous pertu...
John L. Maryak, Daniel C. Chin