Efficient Hyperparameter Optimization under Multi-Source Covariate Shift-Reference-Cited by-同舟云学术

Efficient Hyperparameter Optimization under Multi-Source Covariate Shift

Published:2021-10-26 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 30th ACM International Conference on Information & Knowledge Management
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Author:

Nomura Masahiro¹,Saito Yuta²

Affiliation:

1. CyberAgent, Inc., Tokyo, Japan

2. Hanjuku-kaso, Co., Ltd., Tokyo, Japan

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3459637.3482336

Reference46 articles.

1. Effective Evaluation Using Logged Bandit Feedback from Multiple Loggers

2. James S Bergstra Rémi Bardenet Yoshua Bengio and Balázs Kégl. 2011. Algorithms for Hyper-Parameter Optimization. In Advances in neural information processing systems. 2546--2554. James S Bergstra Rémi Bardenet Yoshua Bengio and Balázs Kégl. 2011. Algorithms for Hyper-Parameter Optimization. In Advances in neural information processing systems. 2546--2554.

3. Ilija Bogunovic Jonathan Scarlett Stefanie Jegelka and Volkan Cevher. 2018. Adversarially robust optimization with gaussian processes. In Advances in neural information processing systems. 5760--5770. Ilija Bogunovic Jonathan Scarlett Stefanie Jegelka and Volkan Cevher. 2018. Adversarially robust optimization with gaussian processes. In Advances in neural information processing systems. 5760--5770.

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