Machine Learning Assisted Evolutionary Multi-Objective Optimization [Guest Editorial]

Guest Editorial: Machine Learning for Signal Processing

Signal processing including analysis, understanding, detection, estimation, and modelling of the events and trends, the way they evolve, and the abnormalities and anomalies affecting them have attracted many researchers around the globe. Signal processing theory originates from mathematical foundation with astonishing applications which help information technologists discover and invent new rea...

Guest Editorial: Machine Learning in Computer Vision

This paper has not been published elsewhere and it has not been submitted simultaneously elsewhere. 2 ABSTRACT In this editorial we briefly discuss interaction between two important areas of artificial intelligence: Computer Vision (CV) and Machine Learning (ML). Although the two fields have a long-standing tradition and can be considered technologically mature, past research in applying ML tec...

Evolutionary Multi-Objective Robust Optimization

Multi-objective Self-optimization of Reconfigurable Designs with Machine Learning

Optimizing reconfigurable designs is a complex task that usually involves manual design analysis and subsequent tweaking. We present a new Multi-Objective Machine Learning Optimizer (MOMLO) which supports self-optimization of reconfigurable designs through automatic analysis and adaptation of design parameters. From a number of benchmark executions, our tool automatically derives the characteri...

GUEST EDITORIAL Computational Intelligence and Machine Learning in Bioinformatics

It is worth noting that a well-known machine learning algorithm (namely, the perceptron, inspired to the behaviour of a neuronal cell [5]), has just been applied to bioinformatics in the eighties to distinguish translation initiation sites in prokaryotic organisms [6], and starting from this early application, a growing number of computational intelligence and machine learning methods has been ...