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» A new quantum behaved particle swarm optimization
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STOC
2007
ACM
98views Algorithms» more  STOC 2007»
16 years 2 months ago
Negative weights make adversaries stronger
The quantum adversary method is one of the most successful techniques for proving lower bounds on quantum query complexity. It gives optimal lower bounds for many problems, has ap...
Peter Høyer, Troy Lee, Robert Spalek
CEC
2008
IEEE
15 years 8 months ago
New evaluation criteria for the convergence of continuous evolutionary algorithms
—The first hitting time (FHT) plays an important role in convergence evaluation for evolutionary algorithms. However, the current criteria of the FHT are mostly under a hypothesi...
Ying Lin, Jian Huang, Jun Zhang
ISCAS
2005
IEEE
114views Hardware» more  ISCAS 2005»
15 years 7 months ago
Structured stochastic optimization strategies for problems with ill-conditioned error surfaces
—This paper compares the performance of several structured optimization strategies in adaptive signal processing problems that are characterized by ill-conditioned error surfaces...
S. Pal, Dean J. Krusienski, W. Kenneth Jenkins
ICASSP
2011
IEEE
14 years 5 months ago
Adaptive modelling with tunable RBF network using multi-innovation RLS algorithm assisted by swarm intelligence
— In this paper, we propose a new on-line learning algorithm for the non-linear system identification: the swarm intelligence aided multi-innovation recursive least squares (SIM...
Hao Chen, Yu Gong, Xia Hong
PPSN
2004
Springer
15 years 7 months ago
Optimization via Parameter Mapping with Genetic Programming
Abstract. This paper describes a new approach for parameter optimization that uses a novel representation for the parameters to be optimized. By using genetic programming, the new ...
João Carlos Figueira Pujol, Riccardo Poli