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ICTAI
2010
IEEE
8 years 8 months ago
Metropolis Particle Swarm Optimization Algorithm with Mutation Operator for Global Optimization Problems
When a local optimal solution is reached with classical Particle Swarm Optimization (PSO), all particles in the swarm gather around it, and escaping from this local optima becomes...
Lhassane Idoumghar, M. Idrissi-Aouad, Mahmoud Melk...
ICA
2010
Springer
8 years 8 months ago
Strong Sub- and Super-Gaussianity
We introduce the terms strong sub- and super-Gaussianity to refer to the previously introduced class of densities log-concave is x2 and log-convex in x2 respectively. We derive rel...
Jason A. Palmer, Kenneth Kreutz-Delgado, Scott Mak...
EC
2006
97views ECommerce» more  EC 2006»
8 years 10 months ago
A Step Forward in Studying the Compact Genetic Algorithm
The compact Genetic Algorithm (cGA) is an Estimation of Distribution Algorithm that generates offspring population according to the estimated probabilistic model of the parent pop...
Reza Rastegar, Arash Hariri
BMCBI
2006
113views more  BMCBI 2006»
8 years 10 months ago
GibbsST: a Gibbs sampling method for motif discovery with enhanced resistance to local optima
Background: Computational discovery of transcription factor binding sites (TFBS) is a challenging but important problem of bioinformatics. In this study, improvement of a Gibbs sa...
Kazuhito Shida
CEC
2010
IEEE
8 years 10 months ago
Towards scalability in niching methods
— The scaling properties of multimodal optimization methods have seldom been studied, and existing studies often concentrated on the idea that all local optima of a multimodal fu...
Marcel Kronfeld, Andreas Zell
CEC
2010
IEEE
8 years 11 months ago
Local Optima Networks of the Quadratic Assignment Problem
Using a recently proposed model for combinatorial landscapes, Local Optima Networks (LON), we conduct a thorough analysis of two types of instances of the Quadratic Assignment Prob...
Fabio Daolio, Sébastien Vérel, Gabri...
UAI
2003
8 years 11 months ago
On Local Optima in Learning Bayesian Networks
This paper proposes and evaluates the k-greedy equivalence search algorithm (KES) for learning Bayesian networks (BNs) from complete data. The main characteristic of KES is that i...
Jens D. Nielsen, Tomás Kocka, José M...
AAAI
2000
8 years 11 months ago
Dynamic Representations and Escaping Local Optima: Improving Genetic Algorithms and Local Search
Local search algorithms often get trapped in local optima. Algorithms such as tabu search and simulated annealing 'escape' local optima by accepting nonimproving moves. ...
Laura Barbulescu, Jean-Paul Watson, L. Darrell Whi...
ECAI
2008
Springer
9 years 1 days ago
Structure Learning of Markov Logic Networks through Iterated Local Search
Many real-world applications of AI require both probability and first-order logic to deal with uncertainty and structural complexity. Logical AI has focused mainly on handling com...
Marenglen Biba, Stefano Ferilli, Floriana Esposito
AIPS
2008
9 years 18 days ago
Stochastic Enforced Hill-Climbing
Enforced hill-climbing is an effective deterministic hillclimbing technique that deals with local optima using breadth-first search (a process called "basin flooding"). ...
Jia-Hong Wu, Rajesh Kalyanam, Robert Givan
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