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UAI
2001
15 years 8 months ago
Iterative Markov Chain Monte Carlo Computation of Reference Priors and Minimax Risk
We present an iterative Markov chain Monte Carlo algorithm for computing reference priors and minimax risk for general parametric families. Our approach uses MCMC techniques based...
John D. Lafferty, Larry A. Wasserman
WSCG
2004
142views more  WSCG 2004»
15 years 8 months ago
Metropolis Iteration for Global Illumination
This paper presents a stochastic iteration algorithm solving the global illumination problem, where the random sampling is governed by classical importance sampling and also by th...
László Szirmay-Kalos, Bálazs ...
AAAI
1997
15 years 8 months ago
Tabu Search for SAT
In this paper, tabu search for SAT is investigated from an experimental point of view. To this end, TSAT, a basic tabu search algorithm for SAT, is introduced and compared with Se...
Bertrand Mazure, Lakhdar Sais, Éric Gr&eacu...
NIPS
1990
15 years 7 months ago
Convergence of a Neural Network Classifier
In this paper, we show that the LVQ learning algorithm converges to locally asymptotic stable equilibria of an ordinary differential equation. We show that the learning algorithm ...
John S. Baras, Anthony LaVigna
CEC
2008
IEEE
15 years 7 months ago
A technique for the visualization of population-based algorithms
— A technique for the visualization of stochastic population–based algorithms in multidimensional problems with known global minimizers is proposed. The technique employs proje...
Konstantinos E. Parsopoulos, Voula C. Georgopoulos...