Next to prediction accuracy, the interpretability of models is one of the fundamental criteria for machine learning algorithms. While high accuracy learners have intensively been e...
This work focuses on the development of a parallel framework method to improve the effectiveness and the efficiency of the obtained solutions by Multi-objective Evolutionary Algori...
Dipankar Dasgupta, David Camilo Becerra Romero, Al...
This paper deals with the study of the exchange of messages among a set of processors linked through an interconnection network. We focus on general, non-uniform versions of messa...
We show that the asymptotic gain in the time complexity when using collision detection depends heavily on the task by investigating three prominent problems for wireless networks,...
The paper addresses the problem of learning a regression model parameterized by a fixed-rank positive semidefinite matrix. The focus is on the nonlinear nature of the search space...