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» Optimal Monte Carlo Algorithms
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GECCO
2007
Springer
211views Optimization» more  GECCO 2007»
14 years 1 months ago
An extremal optimization search method for the protein folding problem: the go-model example
The protein folding problem consists of predicting the functional (native) structure of the protein given its linear sequence of amino acids. Despite extensive progress made in un...
Alena Shmygelska
DAC
2006
ACM
14 years 8 months ago
Generation of yield-aware Pareto surfaces for hierarchical circuit design space exploration
Pareto surfaces in the performance space determine the range of feasible performance values for a circuit topology in a given technology. We present a non-dominated sorting based ...
Saurabh K. Tiwary, Pragati K. Tiwary, Rob A. Ruten...
CEC
2008
IEEE
14 years 2 months ago
Natural Evolution Strategies
— This paper presents Natural Evolution Strategies (NES), a novel algorithm for performing real-valued ‘black box’ function optimization: optimizing an unknown objective func...
Daan Wierstra, Tom Schaul, Jan Peters, Jürgen...
UAI
2000
13 years 9 months ago
Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks
Particle filters (PFs) are powerful samplingbased inference/learning algorithms for dynamic Bayesian networks (DBNs). They allow us to treat, in a principled way, any type of prob...
Arnaud Doucet, Nando de Freitas, Kevin P. Murphy, ...
GECCO
2010
Springer
207views Optimization» more  GECCO 2010»
14 years 18 days ago
Generalized crowding for genetic algorithms
Crowding is a technique used in genetic algorithms to preserve diversity in the population and to prevent premature convergence to local optima. It consists of pairing each offsp...
Severino F. Galán, Ole J. Mengshoel