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CEC
2009
IEEE
14 years 2 months ago
An adaptive learning particle swarm optimizer for function optimization
— Traditional particle swarm optimization (PSO) suffers from the premature convergence problem, which usually results in PSO being trapped in local optima. This paper presents an...
Changhe Li, Shengxiang Yang
ICANN
2003
Springer
14 years 22 days ago
Optimal Hebbian Learning: A Probabilistic Point of View
Many activity dependent learning rules have been proposed in order to model long-term potentiation (LTP). Our aim is to derive a spike time dependent learning rule from a probabili...
Jean-Pascal Pfister, David Barber, Wulfram Gerstne...
CEC
2010
IEEE
13 years 8 months ago
Adaptive learning particle swarm optimizer-II for global optimization
This paper presents an updated version of the adaptive learning particle swarm optimizer (ALPSO) [6], we call it ALPSO-II. In order to improve the performance of ALPSO on multi-mod...
Changhe Li, Shengxiang Yang
NAACL
2001
13 years 9 months ago
Learning Optimal Dialogue Management Rules by Using Reinforcement Learning and Inductive Logic Programming
Developing dialogue systems is a complex process. In particular, designing efficient dialogue management strategies is often difficult as there are no precise guidelines to develo...
Renaud Lecoeuche
IUI
2012
ACM
12 years 3 months ago
Probabilistic pointing target prediction via inverse optimal control
Numerous interaction techniques have been developed that make “virtual” pointing at targets in graphical user interfaces easier than analogous physical pointing tasks by invok...
Brian D. Ziebart, Anind K. Dey, J. Andrew Bagnell