58 citations · 70 across the 4 of their papers we have counts for
4 papers
A Newton Method for Hausdorff Approximations of the Pareto Front within Multi-objective Evolutionary Algorithms
Hao Wang, Angel E. Rodriguez-Fernandez, Lourdes Uribe +3
A common goal in evolutionary multi-objective optimization is to find suitable finite-size approximations of the Pareto front of a given multi-objective optimization problem. While…
Automatic Model Selection for Neural Networks
David Laredo, Yulin Qin, Oliver Schütze +1
Neural networks and deep learning are changing the way that artificial intelligence is being done. Efficiently choosing a suitable network architecture and fine-tune its hyper-para…
A Neural Network-Evolutionary Computational Framework for Remaining Useful Life Estimation of Mechanical Systems
David Laredo, Zhaoyin Chen, Oliver Schütze +1
This paper presents a framework for estimating the remaining useful life (RUL) of mechanical systems. The framework consists of a multi-layer perceptron and an evolutionary algorit…
Computing a Finite Size Representation of the Set of Approximate Solutions of an MOP
Oliver Schuetze, Carlos A. Coello Coello, Emilia Tantar +1
Recently, a framework for the approximation of the entire set of -efficient solutions (denote by ) of a multi-objective optimization problem with stochastic search algorith…