In this paper we perform an empirical evaluation of supervised learning on highdimensional data. We evaluate performance on three metrics: accuracy, AUC, and squared loss and stud...
— In this paper, we present a distributed computing framework designed to support higher quality of service and fault tolerance for processing deadline-driven tasks in a P2P envi...
Leveraging DHTs (distributed hash table), we propose Ferry, an architecture for content-based publish/subscribe services. With its novel design in subscription installation, subsc...
We consider the problem of learning Gaussian multiresolution (MR) models in which data are only available at the finest scale and the coarser, hidden variables serve both to captu...
Myung Jin Choi, Venkat Chandrasekaran, Alan S. Wil...
The Fast Johnson-Lindenstrauss Transform (FJLT) was recently discovered by Ailon and Chazelle as a novel technique for performing fast dimension reduction with small distortion fr...