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DBQ: A Differentiable Branch Quantizer for Lightweight Deep Neural Networks


Jul 19, 2020
Hassan Dbouk, Hetul Sanghvi, Mahesh Mehendale, Naresh Shanbhag

* Published as a conference paper in ECCV 2020 

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HarDNN: Feature Map Vulnerability Evaluation in CNNs


Feb 25, 2020
Abdulrahman Mahmoud, Siva Kumar Sastry Hari, Christopher W. Fletcher, Sarita V. Adve, Charbel Sakr, Naresh Shanbhag, Pavlo Molchanov, Michael B. Sullivan, Timothy Tsai, Stephen W. Keckler

* 14 pages, 5 figures, a short version accepted for publication in First Workshop on Secure and Resilient Autonomy (SARA) co-located with MLSys2020 

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Accumulation Bit-Width Scaling For Ultra-Low Precision Training Of Deep Networks


Jan 19, 2019
Charbel Sakr, Naigang Wang, Chia-Yu Chen, Jungwook Choi, Ankur Agrawal, Naresh Shanbhag, Kailash Gopalakrishnan

* Published as a conference paper in ICLR 2019 

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Per-Tensor Fixed-Point Quantization of the Back-Propagation Algorithm


Dec 31, 2018
Charbel Sakr, Naresh Shanbhag

* Published as a conference paper in ICLR 2019 

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Understanding the Energy and Precision Requirements for Online Learning


Aug 26, 2016
Charbel Sakr, Ameya Patil, Sai Zhang, Yongjune Kim, Naresh Shanbhag

* 14 pages, 5 figures 4 of which have 2 subfigures 

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Error-Resilient Machine Learning in Near Threshold Voltage via Classifier Ensemble


Jul 03, 2016
Sai Zhang, Naresh Shanbhag


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