A Melting Pot of Evolution and Learning
| Autor: | Sipper, Moshe, Elyasaf, Achiya, Halperin, Tomer, Haramaty, Zvika, Lapid, Raz, Segal, Eyal, Tzruia, Itai, Tamam, Snir Vitrack |
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| Rok vydání: | 2023 |
| Předmět: | |
| Druh dokumentu: | Working Paper |
| Popis: | 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. Comment: To Appear in Proceedings of Genetic Programming Theory & Practice XX, 2023 |
| Databáze: | arXiv |
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