Lithography Hotspot Detection via Heterogeneous Federated Learning with Local Adaptation-Reference-Cited by-同舟云学术

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Lithography Hotspot Detection via Heterogeneous Federated Learning with Local Adaptation

Published:2022-01-17 Issue: Volume: Page:
ISSN:
Container-title:2022 27th Asia and South Pacific Design Automation Conference (ASP-DAC)
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Author:

Lin Xuezhong¹,Pan Jingyu²,Xu Jinming¹,Chen Yiran²,Zhuo Cheng¹

Affiliation:

1. Zhejiang University,Hangzhou,China

2. Duke University,Durham,NC,USA

Funder

National Key R&D Program of China

NSFC

Fundamental Research Funds for the Central Universities

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9712466/9712479/09712491.pdf?arnumber=9712491

Reference17 articles.

1. Federated optimization in heterogeneous networks;li;ArXiv Preprint,2018

2. Layout hotspot detection with feature tensor generation and deep biased learning;yang;IEEE TCAD,2018

3. Optical proximity correction with hierarchical bayes model;matsunawa;Optical Microlithography XXVI,2015

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Communication Efficiency and Non-Independent and Identically Distributed Data Challenge in Federated Learning: A Systematic Mapping Study;Applied Sciences;2024-03-24

2. GitFL: Uncertainty-Aware Real-Time Asynchronous Federated Learning Using Version Control;2023 IEEE Real-Time Systems Symposium (RTSS);2023-12-05

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