Multi-label learning deals with data associated with multiple labels simultaneously. Previous work on multi-label learning assumes that for each instance, the "full" lab...
The weak instance model is a framework to consider the relations in a database as a whole, regardless of the way attributes are grouped in the individual relations. Queries and upd...
We show that there are unimodal fitness functions and genetic algorithm (GA) parameter settings where the GA, when initialized with a random population, will not move close to the...
Abstract--Learning multiple related tasks from data simultaneously can improve predictive performance relative to learning these tasks independently. In this paper we propose a nov...
Jean Baptiste Faddoul, Boris Chidlovskii, Fabien T...
A local algorithm is a distributed algorithm that completes after a constant number of synchronous communication rounds. We present local approximation algorithms for the minimum ...