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IJAR
2006
98views more  IJAR 2006»
15 years 6 months ago
A forward-backward Monte Carlo method for solving influence diagrams
Although influence diagrams are powerful tools for representing and solving complex decisionmaking problems, their evaluation may require an enormous computational effort and this...
Andrés Cano, Manuel Gómez, Seraf&iac...
GECCO
2009
Springer
164views Optimization» more  GECCO 2009»
15 years 4 months ago
Solving iterated functions using genetic programming
An iterated function f(x) is a function that when composed with itself, produces a given expression f(f(x))=g(x). Iterated functions are essential constructs in fractal theory and...
Michael D. Schmidt, Hod Lipson
GECCO
2008
Springer
168views Optimization» more  GECCO 2008»
15 years 7 months ago
Speed-up techniques for solving large-scale bTSP with the Two-Phase Pareto Local Search
We first present a method, called Two-Phase Pareto Local Search, to find a good approximation of the efficient set of the biobjective traveling salesman problem. In the first p...
Thibaut Lust
CP
2007
Springer
16 years 17 days ago
Structural Relaxations by Variable Renaming and Their Compilation for Solving MinCostSAT
Searching for optimal solutions to a problem using lower bounds obtained from a relaxation is a common idea in Heuristic Search and Planning. In SAT and CSPs, however, explicit rel...
Miquel Ramírez, Hector Geffner
CVPR
2011
IEEE
15 years 2 months ago
Particle Filter with State Permutations for Solving Image Jigsaw Puzzles
We deal with an image jigsaw puzzle problem, which is defined as reconstructing an image from a set of square and non-overlapping image patches. It is known that a general instan...
Xingwei Yang, Nagesh Adluru, LonginJan Latecki