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ATAL
2007
Springer
15 years 6 months ago
Approximate state estimation in multiagent settings with continuous or large discrete state spaces
We present a new method for carrying out state estimation in multiagent settings that are characterized by continuous or large discrete state spaces. State estimation in multiagen...
Prashant Doshi
112
Voted
MIRAGE
2007
Springer
15 years 6 months ago
A Note on the Discrete Binary Mumford-Shah Model
Abstract. This paper is concerned itself with the analysis of the twophase Mumford-Shah model also known as the active contour without edges model introduced by Chan and Vese. It c...
Jérôme Darbon
134
Voted
GECCO
2005
Springer
384views Optimization» more  GECCO 2005»
15 years 6 months ago
A case study of process facility optimization using discrete event simulation and genetic algorithm
Optimization problems such as resource allocation, job-shop scheduling, equipment utilization and process scheduling occur in a broad range of processing industries. This paper pr...
Keshav P. Dahal, Stuart Galloway, Graeme M. Burt, ...
110
Voted
ICML
2003
IEEE
15 years 6 months ago
Evolutionary MCMC Sampling and Optimization in Discrete Spaces
The links between genetic algorithms and population-based Markov Chain Monte Carlo (MCMC) methods are explored. Genetic algorithms (GAs) are well-known for their capability to opt...
Malcolm J. A. Strens
87
Voted
NIPS
2007
15 years 2 months ago
Active Preference Learning with Discrete Choice Data
We propose an active learning algorithm that learns a continuous valuation model from discrete preferences. The algorithm automatically decides what items are best presented to an...
Eric Brochu, Nando de Freitas, Abhijeet Ghosh