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2020 – today
- 2024
[j2]Yang Ni
, Danny Abraham, Mariam Issa, Alejandro Hernández-Cano, Mahdi Imani, Pietro Mercati, Mohsen Imani:
Dynamic MAC Protocol for Wireless Spectrum Sharing via Hyperdimensional Self-Learning. IEEE Access 12: 138519-138534 (2024)- [c5]Danny Abraham, Biswadip Maity, Bryan Donyanavard, Nikil D. Dutt:
Back to the Future: Reversible Runtime Neural Network Pruning for Safe Autonomous Systems. DATE 2024: 1-6 - 2023
- [j1]Mike Heddes, Igor Nunes, Pere Vergés, Denis Kleyko, Danny Abraham, Tony Givargis, Alexandru Nicolau, Alexander V. Veidenbaum:
Torchhd: An Open Source Python Library to Support Research on Hyperdimensional Computing and Vector Symbolic Architectures. J. Mach. Learn. Res. 24: 255:1-255:10 (2023) - [c4]Yang Ni, Danny Abraham, Mariam Issa, Yeseong Kim, Pietro Mercati, Mohsen Imani:
Efficient Off-Policy Reinforcement Learning via Brain-Inspired Computing. ACM Great Lakes Symposium on VLSI 2023: 449-453 - [c3]Igor Nunes, Mike Heddes, Pere Vergés, Danny Abraham, Alexander V. Veidenbaum, Alex Nicolau, Tony Givargis:
DotHash: Estimating Set Similarity Metrics for Link Prediction and Document Deduplication. KDD 2023: 1758-1769 - [i2]Igor Nunes, Mike Heddes, Pere Vergés, Danny Abraham, Alexander V. Veidenbaum, Alexandru Nicolau, Tony Givargis:
DotHash: Estimating Set Similarity Metrics for Link Prediction and Document Deduplication. CoRR abs/2305.17310 (2023) - 2022
- [c2]Yang Ni, Mariam Issa, Danny Abraham, Mahdi Imani, Xunzhao Yin, Mohsen Imani:
HDPG: hyperdimensional policy-based reinforcement learning for continuous control. DAC 2022: 1141-1146 - [c1]Mariam Issa, Sina Shahhosseini, Yang Ni, Tianyi Hu, Danny Abraham, Amir M. Rahmani, Nikil D. Dutt, Mohsen Imani:
Hyperdimensional Hybrid Learning on End-Edge-Cloud Networks. ICCD 2022: 652-655 - [i1]Yang Ni, Danny Abraham, Mariam Issa, Yeseong Kim, Pietro Mercati, Mohsen Imani:
QHD: A brain-inspired hyperdimensional reinforcement learning algorithm. CoRR abs/2205.06978 (2022)
Coauthor Index
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