We study the topological simplification of graphs via random embeddings, leading ultimately to a reduction of the Gupta-Newman-Rabinovich-Sinclair (GNRS) L1 embedding conjecture t...
Abstract. We present a new distributed association rule mining (D-ARM) algorithm that demonstrates superlinear speed-up with the number of computing nodes. The algorithm is the fi...
Numerous mathematical approaches have been proposed to determine the optimal checkpoint interval for minimizing total execution time of an application in the presence of failures....
We consider testing graph expansion in the bounded-degree graph model. Specifically, we refer to algorithms for testing whether the graph has a second eigenvalue bounded above by a...
Universally achievable error exponents pertaining to certain families of channels (most notably, discrete memoryless channels (DMC’s)), and various ensembles of random codes, ar...