Quantization-aware interval bound propagation for training certifiably robust quantized neural networks

We study the problem of training and certifying adversarially robust quantized neural networks (QNNs). Quantization is a technique for making neural networks more efficient by running them using low-bit integer arithmetic and is therefore commonly adopted in industry. Recent work has shown that floa...

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Bibliographic Details
Main Authors: LECHNER, Mathias, ZIKELIC, Dorde, CHATTERJEE, Krishnendu, HENZINGER, A. Thomas, RUS, Daniela
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2023
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Online Access:https://ink.library.smu.edu.sg/sis_research/9082
https://ink.library.smu.edu.sg/context/sis_research/article/10085/viewcontent/26747_Article_Text_30810_1_2_20230626.pdf
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Institution: Singapore Management University
Language: English
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