47 citations · 64 across the 5 of their papers we have counts for
5 papers
Efficient Off-Policy Reinforcement Learning via Brain-Inspired Computing
Yang Ni, Danny Abraham, Mariam Issa +3
Reinforcement Learning (RL) has opened up new opportunities to enhance existing smart systems that generally include a complex decision-making process. However, modern RL algorithm…
DeepSketch: A New Machine Learning-Based Reference Search Technique for Post-Deduplication Delta Compression
Jisung Park, Jeoggyun Kim, Yeseong Kim +2
Data reduction in storage systems is becoming increasingly important as an effective solution to minimize the management cost of a data center. To maximize data-reduction efficienc…
Spiking Hyperdimensional Network: Neuromorphic Models Integrated with Memory-Inspired Framework
Zhuowen Zou, Haleh Alimohamadi, Farhad Imani +2
Recently, brain-inspired computing models have shown great potential to outperform today's deep learning solutions in terms of robustness and energy efficiency. Particularly, Spiki…
SHEARer: Highly-Efficient Hyperdimensional Computing by Software-Hardware Enabled Multifold Approximation
Behnam Khaleghi, Sahand Salamat, Anthony Thomas +3
Hyperdimensional computing (HD) is an emerging paradigm for machine learning based on the evidence that the brain computes on high-dimensional, distributed, representations of data…
RAPIDNN: In-Memory Deep Neural Network Acceleration Framework
Mohsen Imani, Mohammad Samragh, Yeseong Kim +3
Deep neural networks (DNN) have demonstrated effectiveness for various applications such as image processing, video segmentation, and speech recognition. Running state-of-the-art D…