A major enterprise in compressed sensing and sparse approximation is the design and analysis of computationally tractable algorithms for recovering sparse, exact or approximate, s...
Jeffrey D. Blanchard, Coralia Cartis, Jared Tanner...
Motivated by several marketplace applications on rapidly growing online social networks, we study the problem of efficient offline matching algorithms for online exchange markets....
Abstract—Hybrid methods are very popular for solving problems from combinatorial optimization. In contrast to this the theoretical understanding of the interplay of different opt...
Tobias Friedrich, Jun He, Nils Hebbinghaus, Frank ...
—This paper presents an approximate Maximum Common Subgraph (MCS) algorithm, specifically for directed, cyclic graphs representing digital circuits. Because of the application d...
Jochem H. Rutgers, Pascal T. Wolkotte, Philip K. F...
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...