A Melting Pot of Evolution and Learning
Abstract
We survey eight recent works by our group, involving the successful blending of evolutionary algorithms with machine learning and deep learning: 1. Binary and Multinomial Classification through Evolutionary Symbolic Regression, 2. Classy Ensemble: A Novel Ensemble Algorithm for Classification, 3. EC-KitY: Evolutionary Computation Tool Kit in Python, 4. Evolution of Activation Functions for Deep Learning-Based Image Classification, 5. Adaptive Combination of a Genetic Algorithm and Novelty Search for Deep Neuroevolution, 6. An Evolutionary, Gradient-Free, Query-Efficient, Black-Box Algorithm for Generating Adversarial Instances in Deep Networks, 7. Foiling Explanations in Deep Neural Networks, 8. Patch of Invisibility: Naturalistic Black-Box Adversarial Attacks on Object Detectors.
Keywords
Cite
@article{arxiv.2306.04971,
title = {A Melting Pot of Evolution and Learning},
author = {Moshe Sipper and Achiya Elyasaf and Tomer Halperin and Zvika Haramaty and Raz Lapid and Eyal Segal and Itai Tzruia and Snir Vitrack Tamam},
journal= {arXiv preprint arXiv:2306.04971},
year = {2023}
}
Comments
To Appear in Proceedings of Genetic Programming Theory & Practice XX, 2023