Pact: Parameterized clipping activation for quantized neural networks J Choi, Z Wang, S Venkataramani, PIJ Chuang, V Srinivasan, ... arXiv preprint arXiv:1805.06085, 2018 | 937 | 2018 |
In-memory computation of a machine-learning classifier in a standard 6T SRAM array J Zhang, Z Wang, N Verma IEEE Journal of Solid-State Circuits 52 (4), 915-924, 2017 | 499 | 2017 |
Accurate and efficient 2-bit quantized neural networks J Choi, S Venkataramani, VV Srinivasan, K Gopalakrishnan, Z Wang, ... Proceedings of Machine Learning and Systems 1, 348-359, 2019 | 186 | 2019 |
A machine-learning classifier implemented in a standard 6T SRAM array J Zhang, Z Wang, N Verma 2016 ieee symposium on vlsi circuits (vlsi-circuits), 1-2, 2016 | 167 | 2016 |
Bridging the accuracy gap for 2-bit quantized neural networks (qnn) J Choi, PIJ Chuang, Z Wang, S Venkataramani, V Srinivasan, ... arXiv preprint arXiv:1807.06964, 2018 | 77 | 2018 |
18.4 A matrix-multiplying ADC implementing a machine-learning classifier directly with data conversion J Zhang, Z Wang, N Verma 2015 IEEE International Solid-State Circuits Conference-(ISSCC) Digest of …, 2015 | 57 | 2015 |
Realizing low-energy classification systems by implementing matrix multiplication directly within an ADC Z Wang, J Zhang, N Verma IEEE transactions on biomedical circuits and systems 9 (6), 825-837, 2015 | 52 | 2015 |
Error adaptive classifier boosting (EACB): Leveraging data-driven training towards hardware resilience for signal inference Z Wang, RE Schapire, N Verma IEEE Transactions on Circuits and Systems I: Regular Papers 62 (4), 1136-1145, 2015 | 48 | 2015 |
A large-area image sensing and detection system based on embedded thin-film classifiers W Rieutort-Louis, T Moy, Z Wang, S Wagner, JC Sturm, N Verma IEEE Journal of Solid-State Circuits 51 (1), 281-290, 2015 | 43 | 2015 |
Overcoming computational errors in sensing platforms through embedded machine-learning kernels Z Wang, KH Lee, N Verma IEEE Transactions on Very Large Scale Integration (VLSI) Systems 23 (8 …, 2014 | 43 | 2014 |
A low-energy machine-learning classifier based on clocked comparators for direct inference on analog sensors Z Wang, N Verma IEEE Transactions on Circuits and Systems I: Regular Papers 64 (11), 2954-2965, 2017 | 36 | 2017 |
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 | 30 | 2018 |
Error-Adaptive Classifier Boosting (EACB): exploiting data-driven training for highly fault-tolerant hardware Z Wang, RE Schapire, N Verma IEEE Int'l Conf. on Acoustics, Speech and Signal Processing (ICASSP), 2014 | 26 | 2014 |
Pact: Parameterized clipping activation for quantized neural networks. arXiv 2018 J Choi, Z Wang, S Venkataramani, PIJ Chuang, V Srinivasan, ... arXiv preprint arXiv:1805.06085, 2018 | 25 | 2018 |
Pact: Parameterized clipping activation for quantized neural networks. arXiv J Choi, Z Wang, S Venkataramani, PIJ Chuang, V Srinivasan, ... arXiv preprint arXiv:1805.06085, 2018 | 18 | 2018 |
A seizure-detection IC employing machine learning to overcome data-conversion and analog-processing non-idealities J Zhang, L Huang, Z Wang, N Verma 2015 IEEE Custom Integrated Circuits Conference (CICC), 1-4, 2015 | 14 | 2015 |
Reducing quantization error in low-energy FIR filter accelerators Z Wang, J Zhang, N Verma 2015 IEEE International Conference on Acoustics, Speech and Signal …, 2015 | 9 | 2015 |
Enabling Hardware Relaxations through Statistical Learning Z Wang, N Verma IEEE Annual Allerton Conference on Communication, Control, and Computing …, 2014 | 7 | 2014 |
Searching for efficient neural architectures for on-device ML on edge TPUs B Akin, S Gupta, Y Long, A Spiridonov, Z Wang, M White, H Xu, P Zhou, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 6 | 2022 |
Facilitating neural network efficiency C Jungwook, K Gopalakrishnan, C Sakr, S Venkataramani, Z Wang US Patent 11,195,096, 2021 | 6 | 2021 |