Safety and Performance, Why not Both? Bi-Objective Optimized Model Compression toward AI Software Deployment

Author:

Zhu Jie1ORCID,Wang Leye1ORCID,Han Xiao2ORCID

Affiliation:

1. Peking University, China

2. Shanghai University of Finance and Economics, China

Publisher

ACM

Reference72 articles.

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5. Tom Brown , Benjamin Mann , Nick Ryder , Melanie Subbiah , Jared  D Kaplan , Prafulla Dhariwal , Arvind Neelakantan , Pranav Shyam , Girish Sastry , Amanda Askell , 2020. Language models are few-shot learners. Advances in neural information processing systems 33 ( 2020 ), 1877–1901. Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, 2020. Language models are few-shot learners. Advances in neural information processing systems 33 (2020), 1877–1901.

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1. Efficient DNN-Powered Software with Fair Sparse Models;Proceedings of the 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis;2024-09-11

2. Safety and Performance, Why Not Both? Bi-Objective Optimized Model Compression Against Heterogeneous Attacks Toward AI Software Deployment;IEEE Transactions on Software Engineering;2024-03

3. FedSlice: Protecting Federated Learning Models from Malicious Participants with Model Slicing;2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE);2023-05

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