Enterprises depend on their information workers finding valuable information to be productive. However, existing enterprise search and recommendation systems can exploit few studi...
This paper addresses the challenging problem of learning from multiple annotators whose labeling accuracy (reliability) differs and varies over time. We propose a framework based ...
For operating system intensive applications, the ability of designers to understand system call performance behavior is essential to achieving high performance. Conventional perfo...
Abstract. Imaging applications such as filtering, image transforms and compression/decompression require vast amounts of computing power when applied to large data sets. These appl...
Benoit A. Gennart, Marc Mazzariol, Vincent Messerl...
We present a theoretical analysis of supervised ranking, providing necessary and sufficient conditions for the asymptotic consistency of algorithms based on minimizing a surrogate...