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Manas Gupta
Manas Gupta
Research Engineer at Agency for Science, Technology & Research (A*STAR), Singapore
Verified email at i2r.a-star.edu.sg
Title
Cited by
Cited by
Year
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
112020
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
92022
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
72022
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
72021
Is complexity required for neural network pruning? a case study on global magnitude pruning
M Gupta, E Camci, VR Keneta, A Vaidyanathan, R Kanodia, CS Foo, ...
arXiv preprint arXiv:2209.14624, 2022
62022
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
22023
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
12023
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
12022
Resource Efficient Neural Networks Using Hessian Based Pruning
J Chong, M Gupta, L Chen
arXiv preprint arXiv:2306.07030, 2023
2023
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
2022
Global Magnitude Pruning With Minimum Threshold Is All We Need
M Gupta, VR Keneta, A Vaidyanathan, R Kanodia, E Camci, CS Foo, J Lin
2021
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