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» Approximate algorithms for neural-Bayesian approaches
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PR
1998
86views more  PR 1998»
14 years 9 months ago
Optimizing the cost matrix for approximate string matching using genetic algorithms
This paper describes a method for optimizing the cost matrix of any approximate string matching algorithm based on the Levenshtein distance. The method, which uses genetic algorit...
Marc Parizeau, Nadia Ghazzali, Jean-Françoi...
CORR
2011
Springer
153views Education» more  CORR 2011»
14 years 4 months ago
Partially Linear Bayesian Estimation with Application to Sparse Approximations
—We address the problem of estimating a random vector X from two sets of measurements Y and Z, such that the estimator is linear in Y . We show that the partially linear minimum ...
Tomer Michaeli, Daniel Sigalov, Yonina C. Eldar
ICDE
2006
IEEE
163views Database» more  ICDE 2006»
15 years 11 months ago
A Sampling-Based Approach to Optimizing Top-k Queries in Sensor Networks
Wireless sensor networks generate a vast amount of data. This data, however, must be sparingly extracted to conserve energy, usually the most precious resource in battery-powered ...
Adam Silberstein, Carla Schlatter Ellis, Jun Yang ...
ICML
2005
IEEE
15 years 10 months ago
Coarticulation: an approach for generating concurrent plans in Markov decision processes
We study an approach for performing concurrent activities in Markov decision processes (MDPs) based on the coarticulation framework. We assume that the agent has multiple degrees ...
Khashayar Rohanimanesh, Sridhar Mahadevan
ATAL
2009
Springer
15 years 4 months ago
Decentralised dynamic task allocation: a practical game: theoretic approach
This paper reports on a novel decentralised technique for planning agent schedules in dynamic task allocation problems. Specifically, we use a Markov game formulation of these pr...
Archie C. Chapman, Rosa Anna Micillo, Ramachandra ...