We present a unifying framework for information theoretic feature selection, bringing almost two decades of research on heuristic filter criteria under a single theoretical inter...
Gavin Brown, Adam Pocock, Ming-Jie Zhao, Mikel Luj...
Abstract. In this paper, we propose a general framework for designing fully polynomial time approximation schemes for combinatorial optimization problems, in which more than one ob...
We provide a unifying geometric framework for the analysis of general classes of duality schemes and penalty methods for nonconvex constrained optimization problems. We present a ...
The optimal and distributed provisioning of high throughput in mesh networks is known as a fundamental but hard problem. The situation is exacerbated in a wireless setting due to t...
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...