Learning useful and predictable features from past workloads and exploiting them well is a major source of improvement in many operating system problems. We review known parallel ...
Abstract. Most of the work in machine learning assume that examples are generated at random according to some stationary probability distribution. In this work we study the problem...
Abstract. Since 1994, the Alexandria Digital Library Project has developed three prototype digital libraries for georeferenced information. This paper describes the most recent of ...
James Frew, Michael Freeston, Nathan Freitas, Lind...
Techniques for efficiently evaluating future time Linear Temporal Logic (abbreviated LTL) formulae on finite execution traces are presented. While the standard models of LTL are i...
We study a novel problem of social context summarization for Web documents. Traditional summarization research has focused on extracting informative sentences from standard docume...
Zi Yang, Keke Cai, Jie Tang, Li Zhang, Zhong Su, J...