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Design of Loss Functions for Solving Inverse Problems using Deep Learning
(Computational Science – ICCS 2020, 202005)Solving inverse problems is a crucial task in several applications that strongly a ffect our daily lives, including multiple engineering fields, military operations, and/or energy production. There exist different methods ... 
Kernels of Mallows Models under the Hamming Distance for solving the Quadratic Assignment Problem
(Swarm and Evolutionary Computation, 202007)The Quadratic Assignment Problem (QAP) is a wellknown permutationbased combinatorial optimization problem with real applications in industrial and logistics environments. Motivated by the challenge that this NPhard ... 
An adaptive neuroevolutionbased hyperheuristic
(The Genetic and Evolutionary Computation Conference, 2020)According to the NoFreeLunch theorem, an algorithm that performs efficiently on any type of problem does not exist. In this sense, algorithms that exploit problemspecific knowledge usually outperform more generic ... 
Evolving Gaussian Process Kernels for Translation Editing Effort Estimation
(Learning and Intelligent Optimization, 2019)In many Natural Language Processing problems the combination of machine learning and optimization techniques is essential. One of these problems is estimating the effort required to improve, under direct human supervision, ... 
Bayesian Optimization Approaches for Massively Multimodal Problems
(Learning and Intelligent Optimization, 2019)The optimization of massively multimodal functions is a challenging task, particularly for problems where the search space can lead the op timization process to local optima. While evolutionary algorithms have been ...