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» Solving the maximum clique problem by k-opt local search
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AAAI
2006
13 years 8 months ago
Solving MAP Exactly by Searching on Compiled Arithmetic Circuits
The MAP (maximum a posteriori hypothesis) problem in Bayesian networks is to find the most likely states of a set of variables given partial evidence on the complement of that set...
Jinbo Huang, Mark Chavira, Adnan Darwiche
SAC
2004
ACM
14 years 26 days ago
Solving the error correcting code problem with parallel hybrid heuristics
Some telecommunication systems can not afford the cost of repeating a corrupted message. Instead, the message should be somewhat “corrected” by the receiver. In these cases a...
Enrique Alba, J. Francisco Chicano
AAAI
2000
13 years 8 months ago
Iterative Flattening: A Scalable Method for Solving Multi-Capacity Scheduling Problems
One challenge for research in constraint-based scheduling has been to produce scalable solution procedures under fairly general representational assumptions. Quite often, the comp...
Amedeo Cesta, Angelo Oddi, Stephen F. Smith
ICTAI
2006
IEEE
14 years 1 months ago
Efficient Search Using Bitboard Models
This paper shows a way to speed up search by using an encoding at bit level to model a particular domain. A bitboard is an unsigned integer whose bits have been given an interpret...
Pablo San Segundo, Ramón Galán, Fern...
GECCO
2008
Springer
171views Optimization» more  GECCO 2008»
13 years 8 months ago
An EDA based on local markov property and gibbs sampling
The key ideas behind most of the recently proposed Markov networks based EDAs were to factorise the joint probability distribution in terms of the cliques in the undirected graph....
Siddhartha Shakya, Roberto Santana