Evo* 2023 -- Late-Breaking Abstracts Volume
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Abstract (arXiv)
Volume with the Late-Breaking Abstracts submitted to the Evo* 2023 Conference, held in Brno (Czech Republic), from 12 to 14 of April. These papers present ongoing research and preliminary results investigating on the application of different approaches of Bioinspired Methods (mainly Evolutionary Computation) to different problems, most of them real world ones.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 11 of its 86 references that are in the map. First posted on arXiv 20 Mar 2024.
Builds on
11 of 86 references.
References · 11
- 2016"Why Should I Trust You?": Explaining the Predictions of Any Classifiercited by 5,040
- 2018The Surprising Creativity of Digital Evolution: A Collection of Anecdotes from the Evolutionary Computation and Artificial Life Research Communitiescited by 78
- 2020Evolutionary learning of interpretable decision treescited by 14
- 2021Model Learning with Personalized Interpretability Estimation (ML-PIE)cited by 9
- 2022Quality Diversity Evolutionary Learning of Decision Treescited by 7
- 2021Multi-Stage Residual Hiding for Image-into-Audio Steganographycited by 6
- 2021PixInWav: Residual Steganography for Hiding Pixels in Audiocited by 5
- 2022Interpretable AI for policy-making in pandemicscited by 5
- 2022Towards Explainable Metaheuristic: Mining Surrogate Fitness Models for Importance of Variablescited by 4
- 2021Source Mixing and Separation Robust Audio Steganographycited by 2
- 2021Backtracking (the) Algorithms on the Hamiltonian Cycle Problemcited by 1
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