Charbel Sakr
Charbel Sakr
Graduate Research Assistant, University of Illinois at Urbana-Champaign
Verified email at illinois.edu - Homepage
Title
Cited by
Cited by
Year
Analytical guarantees on numerical precision of deep neural networks
C Sakr, Y Kim, N Shanbhag
International Conference on Machine Learning, 3007-3016, 2017
412017
Predictivenet: An energy-efficient convolutional neural network via zero prediction
Y Lin, C Sakr, Y Kim, N Shanbhag
2017 IEEE international symposium on circuits and systems (ISCAS), 1-4, 2017
302017
Per-Tensor Fixed-Point Quantization of the Back-Propagation Algorithm
C Sakr, N Shanbhag
International Conference on Learning Representations, 2019
162019
Minimum precision requirements for the SVM-SGD learning algorithm
C Sakr, A Patil, S Zhang, Y Kim, N Shanbhag
2017 IEEE International Conference on Acoustics, Speech and Signal …, 2017
132017
An analytical method to determine minimum per-layer precision of deep neural networks
C Sakr, N Shanbhag
2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018
112018
Accumulation Bit-Width Scaling For Ultra-Low Precision Training Of Deep Networks
C Sakr, N Wang, CY Chen, J Choi, A Agrawal, N Shanbhag, ...
International Conference on Learning Representations, 2019
62019
True gradient-based training of deep binary activated neural networks via continuous binarization
C Sakr, J Choi, Z Wang, K Gopalakrishnan, N Shanbhag
2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018
62018
Understanding the energy and precision requirements for online learning
C Sakr, A Patil, S Zhang, Y Kim, N Shanbhag
arXiv preprint arXiv:1607.00669, 2016
52016
Reducing the energy cost of inference via in-sensor information processing
S Zhang, M Kang, C Sakr, N Shanbhag
arXiv preprint arXiv:1607.00667, 2016
42016
HarDNN: Feature Map Vulnerability Evaluation in CNNs
A Mahmoud, SKS Hari, CW Fletcher, SV Adve, C Sakr, N Shanbhag, ...
arXiv preprint arXiv:2002.09786, 2020
22020
Minimum Precision Requirements for Deep Learning with Biomedical Datasets
C Sakr, N Shanbhag
2018 IEEE Biomedical Circuits and Systems Conference (BioCAS), 1-4, 2018
22018
KeyRAM: A 0.34 uJ/decision 18 k decisions/s Recurrent Attention In-memory Processor for Keyword Spotting
H Dbouk, SK Gonugondla, C Sakr, NR Shanbhag
2020 IEEE Custom Integrated Circuits Conference (CICC), 1-4, 2020
2020
Facilitating neural network efficiency
C Jungwook, K Gopalakrishnan, C Sakr, S Venkataramani, Z Wang
US Patent App. 15/792,733, 2019
2019
Minimum Precision Requirements of General Margin Hyperplane Classifiers
C Sakr, Y Kim, N Shanbhag
IEEE Journal on Emerging and Selected Topics in Circuits and Systems 9 (2 …, 2019
2019
Analytical guarantees for reduced precision fixed-point margin hyperplane classifiers
C Sakr
2017
FEATURE MAP VULNERABILITY EVALUATION IN CNNS
A Mahmoud, SKS Hari, CW Fletcher, SV Adve, C Sakr, N Shanbhag, ...
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