We present a new cache oblivious scheme for iterative stencil computations that performs beyond system bandwidth limitations as though gigabytes of data could reside in an enormou...
Robert Strzodka, Mohammed Shaheen, Dawid Pajak, Ha...
Artemis is a modular application designed for analyzing and troubleshooting the performance of large clusters running datacenter services. Artemis is composed of four modules: (1)...
Gabriela F. Cretu-Ciocarlie, Mihai Budiu, Mois&eac...
This paper develops the concept of usefulness in the context of supervised learning. We argue that usefulness can be used to improve the performance of classification rules (as me...
Gholamreza Nakhaeizadeh, Charles Taylor, Carsten L...
The main focus of this paper is to present a method of reusing motion captured data by learning a generative model of motion. The model allows synthesis and blending of cyclic moti...
We describe an ensemble approach to learning1 salient regions from data partitioned according to the2 distributed processing requirements of large-scale sim-3 ulations. The volume...
Larry Shoemaker, Robert E. Banfield, Larry O. Hall...