231 search results - page 39 / 47 » Controlling Particle Swarm Optimization with Learned Paramet... |
MMB
2012
Springer
12 years 2 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...
IROS
2009
IEEE
14 years 1 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...
NIPS
2004
13 years 8 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...
ICML
2005
IEEE
14 years 7 months 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 ...
AE
2003
Springer
14 years 7 days 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...