| Analytical guarantees on numerical precision of deep neural networks C Sakr, Y Kim, N Shanbhag International Conference on Machine Learning, 3007-3016, 2017 | 113 | 2017 |
| 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 | 92 | 2017 |
| Per-Tensor Fixed-Point Quantization of the Back-Propagation Algorithm C Sakr, N Shanbhag International Conference on Learning Representations, 2019 | 54 | 2019 |
| 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 | 48 | 2018 |
| Fundamental limits on the precision of in-memory architectures SK Gonugondla, C Sakr, H Dbouk, NR Shanbhag Proceedings of the 39th International Conference on Computer-Aided Design, 1-9, 2020 | 43 | 2020 |
| 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 | 43 | 2020 |
| Optimizing Selective Protection for CNN Resilience. A Mahmoud, SKS Hari, CW Fletcher, SV Adve, C Sakr, NR Shanbhag, ... ISSRE, 127-138, 2021 | 40 | 2021 |
| 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 | 40 | 2019 |
| 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 | 31 | 2018 |
| Optimal clipping and magnitude-aware differentiation for improved quantization-aware training C Sakr, S Dai, R Venkatesan, B Zimmer, W Dally, B Khailany International Conference on Machine Learning, 19123-19138, 2022 | 29 | 2022 |
| 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 | 25 | 2017 |
| A 0.44-μJ/dec, 39.9-μs/dec, Recurrent Attention In-Memory Processor for Keyword Spotting H Dbouk, SK Gonugondla, C Sakr, NR Shanbhag IEEE Journal of Solid-State Circuits 56 (7), 2234-2244, 2020 | 24 | 2020 |
| A 95.6-TOPS/W deep learning inference accelerator with per-vector scaled 4-bit quantization in 5 nm B Keller, R Venkatesan, S Dai, SG Tell, B Zimmer, C Sakr, WJ Dally, ... IEEE Journal of Solid-State Circuits 58 (4), 1129-1141, 2023 | 19 | 2023 |
| 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 | 18 | 2020 |
| Signal processing methods to enhance the energy efficiency of in-memory computing architectures C Sakr, NR Shanbhag IEEE Transactions on Signal Processing 69, 6462-6472, 2021 | 17 | 2021 |
| Fundamental limits on energy-delay-accuracy of in-memory architectures in inference applications SK Gonugondla, C Sakr, H Dbouk, NR Shanbhag IEEE Transactions on Computer-Aided Design of Integrated Circuits and …, 2021 | 17 | 2021 |
| Facilitating neural network efficiency C Jungwook, K Gopalakrishnan, C Sakr, S Venkataramani, Z Wang US Patent 11,195,096, 2021 | 7 | 2021 |
| 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 | 6 | 2016 |
| Vapr: Variable-precision tensors to accelerate robot motion planning YS Hsiao, SKS Hari, B Sundaralingam, J Yik, T Tambe, C Sakr, ... 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2023 | 4 | 2023 |
| Minimum precision requirements for deep learning with biomedical datasets C Sakr, N Shanbhag 2018 IEEE Biomedical Circuits and Systems Conference (BioCAS), 1-4, 2018 | 3 | 2018 |
Naresh ShanbhagProfessor of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign在 illinois.edu 的电子邮件经过验证
