The k-means algorithm is a well-known method for partitioning n points that lie in the d-dimensional space into k clusters. Its main features are simplicity and speed in practice....
We present an "adaptive multi-start" genetic algorithm for the Euclidean traveling salesman problem that uses a population of tours locally optimized by the Lin-Kernigha...
Dan Bonachea, Eugene Ingerman, Joshua Levy, Scott ...
Most compiler optimizations and software productivity tools rely on information about the effects of pointer dereferences in a program. The purpose of points-to analysis is to com...
We continue the study of approximating the number of distinct elements in a data stream of length n to within a (1? ) factor. It is known that if the stream may consist of arbitra...
This paper presents a hardware-optimized variant of the well-known Gaussian elimination over GF(2) and its highly efficient implementation. The proposed hardware architecture, we...