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ES-ENAS: Blackbox Optimization over Hybrid Spaces via Combinatorial and Continuous Evolution. (arXiv:2101.07415v5 [cs.LG] UPDATED)
April 29, 2022, 1:12 a.m. | Xingyou Song, Krzysztof Choromanski, Jack Parker-Holder, Yunhao Tang, Qiuyi Zhang, Daiyi Peng, Deepali Jain, Wenbo Gao, Aldo Pacchiano, Tamas Sarlos,
cs.LG updates on arXiv.org arxiv.org
In this paper, we approach the problem of optimizing blackbox functions over
large hybrid search spaces consisting of both combinatorial and continuous
parameters. We demonstrate that previous evolutionary algorithms which rely on
mutation-based approaches, while flexible over combinatorial spaces, suffer
from a curse of dimensionality in high dimensional continuous spaces both
theoretically and empirically, which thus limits their scope over hybrid search
spaces as well. In order to combat this curse, we propose ES-ENAS, a simple and
modular joint optimization …
More from arxiv.org / cs.LG updates on arXiv.org
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