We address the problem of computing approximate answers to continuous sliding-window joins over data streams when the available memory may be insufficient to keep the entire join...
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...
There are many systems and techniques that address stochastic scheduling problems, based on distinct and sometimes opposite approaches, especially in terms of how scheduling and s...
Julien Bidot, Thierry Vidal, Philippe Laborie, J. ...
The inference of consensus from a set of evolutionary trees is a fundamental problem in a number of fields such as biology and historical linguistics, and many models for inferrin...
In this paper, we define and study a new opinionated text data analysis problem called Latent Aspect Rating Analysis (LARA), which aims at analyzing opinions expressed about an e...