We present a novel Locality-Sensitive Hashing scheme for the Approximate Nearest Neighbor Problem under ÐÔ norm, based on Ôstable distributions. Our scheme improves the running...
Mayur Datar, Nicole Immorlica, Piotr Indyk, Vahab ...
We investigate the shortest common superstring problem (SCSSP). As SCSSP is APX-complete it cannot be approximated within an arbitrarily small performance ratio. One heuristic tha...
Various problems in machine learning, databases, and statistics involve pairwise distances among a set of objects. It is often desirable for these distances to satisfy the propert...
Typical real-time scheduling theory has addressed deadline and energy constraints as well as deadline and reward constraints simultaneously in the past. However, we believe that e...
Much effort is spent everyday by programmers in trying to reduce long, failing execution traces to the cause of the error. We present a new algorithm for error cause localization ...