| Qlp: Deep q-learning for pruning deep neural networks E Camci, M Gupta, M Wu, J Lin IEEE Transactions on Circuits and Systems for Video Technology 32 (10), 6488 …, 2022 | 15 | 2022 |
| Learning to Prune Deep Neural Networks via Reinforcement Learning M Gupta, S Aravindan, A Kalisz, V Chandrasekhar, L Jie ICML 2020 Workshop on Automated Machine Learning (AutoML 2020), 2020 | 14 | 2020 |
| Hebbnet: A simplified hebbian learning framework to do biologically plausible learning M Gupta, AM Ambikapathi, S Ramasamy ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021 | 12 | 2021 |
| Is complexity required for neural network pruning? a case study on global magnitude pruning M Gupta, E Camci, VR Keneta, A Vaidyanathan, R Kanodia, A James, ... 2024 IEEE Conference on Artificial Intelligence (CAI), 747-754, 2024 | 11 | 2024 |
| Is bio-inspired learning better than backprop? benchmarking bio learning vs. backprop M Gupta, SK Modi, H Zhang, JH Lee, JH Lim arXiv preprint arXiv:2212.04614, 2022 | 10 | 2022 |
| Towards explainable recommendation via bert-guided explanation generator H Zhan, L Li, S Li, W Liu, M Gupta, AC Kot ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023 | 4 | 2023 |
| Improving transparency and representational generalizability through parallel continual learning M Paknezhad, H Rengarajan, C Yuan, S Suresh, M Gupta, S Ramasamy, ... Neural Networks 161, 449-465, 2023 | 1 | 2023 |
| Investigating robustness of biological vs. backprop based learning Y Zhou, M Wang, M Gupta, A Ambikapathi, PN Suganthan, S Ramasamy ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022 | 1 | 2022 |
| PaRT: Parallel Learning Towards Robust and Transparent AI M Paknezhad, H Rengarajan, C Yuan, S Suresh, M Gupta, S Ramasamy, ... arXiv preprint arXiv:2201.09534, 2022 | 1 | 2022 |
| From Algorithm to Hardware: A Survey on Efficient and Safe Deployment of Deep Neural Networks X Geng, Z Wang, C Chen, Q Xu, K Xu, C Jin, M Gupta, X Yang, Z Chen, ... IEEE Transactions on Neural Networks and Learning Systems, 2024 | | 2024 |
| Resource Efficient Neural Networks Using Hessian Based Pruning J Chong, M Gupta, L Chen arXiv preprint arXiv:2306.07030, 2023 | | 2023 |
| Global Magnitude Pruning With Minimum Threshold Is All We Need M Gupta, VR Keneta, A Vaidyanathan, R Kanodia, E Camci, CS Foo, J Lin | | |
Jie LinUnknown affiliation確認したメール アドレス: lrdtech.com