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CVPR
2009
IEEE
14 years 7 months ago
Markov Chain Monte Carlo Combined with Deterministic Methods for Markov Random Field Optimization
Many vision problems have been formulated as en- ergy minimization problems and there have been signif- icant advances in energy minimization algorithms. The most widely-used energ...
Wonsik Kim (Seoul National University), Kyoung Mu ...
GECCO
2006
Springer
173views Optimization» more  GECCO 2006»
14 years 8 days ago
Pareto-coevolutionary genetic programming classifier
The conversion and extension of the Incremental ParetoCoevolution Archive algorithm (IPCA) into the domain of Genetic Programming classifier evolution is presented. In order to ac...
Michal Lemczyk, Malcolm I. Heywood
EUROCAST
2007
Springer
132views Hardware» more  EUROCAST 2007»
14 years 15 days ago
Using Omnidirectional BTS and Different Evolutionary Approaches to Solve the RND Problem
RND (Radio Network Design) is an important problem in mobile telecommunications (for example in mobile/cellular telephony), being also relevant in the rising area of sensor network...
Miguel A. Vega-Rodríguez, Juan Antonio G&oa...
ICML
2000
IEEE
14 years 9 months ago
Reinforcement Learning in POMDP's via Direct Gradient Ascent
This paper discusses theoretical and experimental aspects of gradient-based approaches to the direct optimization of policy performance in controlled ??? ?s. We introduce ??? ?, a...
Jonathan Baxter, Peter L. Bartlett
WSCG
2004
142views more  WSCG 2004»
13 years 10 months ago
Metropolis Iteration for Global Illumination
This paper presents a stochastic iteration algorithm solving the global illumination problem, where the random sampling is governed by classical importance sampling and also by th...
László Szirmay-Kalos, Bálazs ...