88 citations · 119 across the 13 of their papers we have counts for
3 papers · 1 filter
Federated Learning with Spiking Neural Networks
Yeshwanth Venkatesha, Youngeun Kim, Leandros Tassiulas +1
As neural networks get widespread adoption in resource-constrained embedded devices, there is a growing need for low-power neural systems. Spiking Neural Networks (SNNs)are emergin…
PrivateSNN: Privacy-Preserving Spiking Neural Networks
Youngeun Kim, Yeshwanth Venkatesha, Priyadarshini Panda
How can we bring both privacy and energy-efficiency to a neural system? In this paper, we propose PrivateSNN, which aims to build low-power Spiking Neural Networks (SNNs) from a pr…
Activation Density based Mixed-Precision Quantization for Energy Efficient Neural Networks
Karina Vasquez, Yeshwanth Venkatesha, Abhiroop Bhattacharjee +2
As neural networks gain widespread adoption in embedded devices, there is a need for model compression techniques to facilitate deployment in resource-constrained environments. Qua…