Pareto Local Search is Competitive with Evolutionary Algorithms for Multi-Objective Neural Architecture Search-Reference-Cited by-同舟云学术

Pareto Local Search is Competitive with Evolutionary Algorithms for Multi-Objective Neural Architecture Search

Published:2023-07-12 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the Genetic and Evolutionary Computation Conference
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Author:

Phan Quan Minh¹²^ORCID,Luong Ngoc Hoang¹²^ORCID

Affiliation:

1. University of Information Technology (UIT), Ho Chi Minh City, Vietnam

2. Vietnam National University - Ho Chi Minh City (VNU-HCM), Ho Chi Minh City, Vietnam

Funder

Vingroup Innovation Foundation (VINIF)

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3583131.3590395

Reference35 articles.

1. Noor Awad , Neeratyoy Mallik , and Frank Hutter . 2020 . Differential Evolution for Neural Architecture Search . In Proceedings of the 1st workshop on neural architecture search(@ICLR'20) . Noor Awad, Neeratyoy Mallik, and Frank Hutter. 2020. Differential Evolution for Neural Architecture Search. In Proceedings of the 1st workshop on neural architecture search(@ICLR'20).

2. The balance between proximity and diversity in multiobjective evolutionary algorithms

3. Finding Knees in Multi-objective Optimization

4. A fast and elitist multiobjective genetic algorithm: NSGA-II

5. Xuanyi Dong and Yi Yang . 2020 . NAS-Bench-201: Extending the Scope of Reproducible Neural Architecture Search . In International Conference on Learning Representations, ICLR 2020. OpenReview.net, Addis Ababa, Ethiopia. Xuanyi Dong and Yi Yang. 2020. NAS-Bench-201: Extending the Scope of Reproducible Neural Architecture Search. In International Conference on Learning Representations, ICLR 2020. OpenReview.net, Addis Ababa, Ethiopia.

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