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GECCO
2008
Springer
168views Optimization» more  GECCO 2008»
13 years 8 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
STOC
2004
ACM
126views Algorithms» more  STOC 2004»
14 years 7 months ago
Bypassing the embedding: algorithms for low dimensional metrics
The doubling dimension of a metric is the smallest k such that any ball of radius 2r can be covered using 2k balls of raThis concept for abstract metrics has been proposed as a na...
Kunal Talwar
SDM
2012
SIAM
245views Data Mining» more  SDM 2012»
11 years 9 months ago
Deterministic CUR for Improved Large-Scale Data Analysis: An Empirical Study
Low-rank approximations which are computed from selected rows and columns of a given data matrix have attracted considerable attention lately. They have been proposed as an altern...
Christian Thurau, Kristian Kersting, Christian Bau...
TSP
2008
151views more  TSP 2008»
13 years 7 months ago
Convergence Analysis of Reweighted Sum-Product Algorithms
Markov random fields are designed to represent structured dependencies among large collections of random variables, and are well-suited to capture the structure of real-world sign...
Tanya Roosta, Martin J. Wainwright, Shankar S. Sas...
NCA
2008
IEEE
13 years 7 months ago
Neurodynamic programming: a case study of the traveling salesman problem
The paper focuses on the study of solving the large-scale traveling salesman problem (TSP) based on neurodynamic programming. From this perspective, two methods, temporal differenc...
Jia Ma, Tao Yang, Zeng-Guang Hou, Min Tan, Derong ...