231 search results - page 39 / 47 » Controlling Particle Swarm Optimization with Learned Paramet... |
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MMB
2012
Springer
13 years 7 months ago
2012
Springer
Abstract. During development, processor architectures can be tuned and configured by many different parameters. For benchmarking, automatic design space explorations (DSEs) with h...
114
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IROS
2009
IEEE
15 years 6 months ago
2009
IEEE
— Partially Observable Markov Decision Processes (POMDPs) provide a rich mathematical model to handle realworld sequential decision processes but require a known model to be solv...
102
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NIPS
2004
15 years 1 months ago
2004
Log-concavity is an important property in the context of optimization, Laplace approximation, and sampling; Bayesian methods based on Gaussian process priors have become quite pop...
98
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ICML
2005
IEEE
16 years 14 days ago
2005
IEEE
Unsupervised learning methods often involve summarizing the data using a small number of parameters. In certain domains, only a small subset of the available data is relevant for ...
93
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AE
2003
Springer
15 years 4 months ago
2003
Springer
The ideas proposed in this work are aimed to describe a novel approach based on artificial life (alife) environments for on-line adaptive optimisation of dynamical systems. The bas...