In this paper, we propose an iterative algorithm for multiple regression with fuzzy variables.While using the standard least-squares criterion as a performance index, we pose the ...
Andrzej Bargiela, Witold Pedrycz, Tomoharu Nakashi...
We propose the use of a new algorithm to solve multiobjective optimization problems. Our proposal adapts the well-known scatter search template for single objective optimization to...
Antonio J. Nebro, Francisco Luna, Enrique Alba, Be...
In this paper, we develop algorithms for distributed computation of averages of the node data over networks with bandwidth/power constraints or large volumes of data. Distributed ...
We consider the problem of learning incoherent sparse and lowrank patterns from multiple tasks. Our approach is based on a linear multi-task learning formulation, in which the spa...
: The paper presents results on the runtime complexity of two ant colony optimization (ACO) algorithms: Ant System, the oldest ACO variant, and GBAS, the first ACO variant for whic...