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10/04/2022
Coordinated Science Laboratory 70th Anniversary Symposium: The Future of Computing
In 2021, the Coordinated Science Laboratory CSL, an Interdisciplinary Re...
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07/19/2020
DBQ: A Differentiable Branch Quantizer for Lightweight Deep Neural Networks
Deep neural networks have achieved state-of-the art performance on vario...
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05/05/2020
Nanotechnology-inspired Information Processing Systems of the Future
Nanoscale semiconductor technology has been a key enabler of the computi...
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02/22/2020
HarDNN: Feature Map Vulnerability Evaluation in CNNs
As Convolutional Neural Networks (CNNs) are increasingly being employed ...
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01/19/2019
Accumulation Bit-Width Scaling For Ultra-Low Precision Training Of Deep Networks
Efforts to reduce the numerical precision of computations in deep learni...
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12/31/2018
Per-Tensor Fixed-Point Quantization of the Back-Propagation Algorithm
The high computational and parameter complexity of neural networks makes...
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10/24/2016
A 481pJ/decision 3.4M decision/s Multifunctional Deep In-memory Inference Processor using Standard 6T SRAM Array
This paper describes a multi-functional deep in-memory processor for inf...
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07/03/2016
Understanding the Energy and Precision Requirements for Online Learning
It is well-known that the precision of data, hyperparameters, and intern...
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07/03/2016