ISNN
2009
Springer
13 years 11 months ago
2009
Springer
Quantum evolutionary algorithm (QEA) is proposed on the basis of the concept and principles of quantum computing, which is a classical metaheuristic algorithm for the approximate s...
GECCO
2009
Springer
13 years 11 months ago
2009
Springer
Genetic algorithms are often applied to combinatorial optimization problems, the most popular one probably being the traveling salesperson problem. In contrast to permutations use...
COCOA
2009
Springer
13 years 11 months ago
2009
Springer
Combinatorial optimization problems have recently emerged in the design of controllers for OLED displays. The objective is to decompose an image into subframes minimizing the addre...
SODA
2010
ACM
14 years 1 months ago
2010
ACM
The quadratic assignment problem (QAP) is a central problem in combinatorial optimization. Several famous computationally hard tasks, such as graph matching, partitioning, and the...
ICALP
2009
Springer
14 years 4 months ago
2009
Springer
Traditionally, combinatorial optimization problems (such as maximum flow, maximum matching, etc.) have been studied for networks where each link has a fixed capacity. Recent resear...
STOC
2002
ACM
14 years 4 months ago
2002
ACM
STOC
2004
ACM
14 years 4 months ago
2004
ACM
We present a probabilistic analysis for a large class of combinatorial optimization problems containing, e.g., all binary optimization problems defined by linear constraints and a...
ICML
2007
IEEE
14 years 5 months ago
2007
IEEE
We study the problem of learning kernel machines transductively for structured output variables. Transductive learning can be reduced to combinatorial optimization problems over a...
ECCV
2006
Springer
14 years 6 months ago
2006
Springer
Abstract. Bayesian inference provides a powerful framework to optimally integrate statistically learned prior knowledge into numerous computer vision algorithms. While the Bayesian...