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05/11/2023
Divide-and-Conquer the NAS puzzle in Resource Constrained Federated Learning Systems
Federated Learning (FL) is a privacy-preserving distributed machine lear...
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11/26/2022
Exploring Temporal Information Dynamics in Spiking Neural Networks
Most existing Spiking Neural Network (SNN) works state that SNNs may uti...
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07/04/2022
Lottery Ticket Hypothesis for Spiking Neural Networks
Spiking Neural Networks (SNNs) have recently emerged as a new generation...
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04/11/2022
MIME: Adapting a Single Neural Network for Multi-task Inference with Memory-efficient Dynamic Pruning
Recent years have seen a paradigm shift towards multi-task learning. Thi...
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03/24/2022
Addressing Client Drift in Federated Continual Learning with Adaptive Optimization
Federated learning has been extensively studied and is the prevalent met...
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01/31/2022
Rate Coding or Direct Coding: Which One is Better for Accurate, Robust, and Energy-efficient Spiking Neural Networks?
Recent Spiking Neural Networks (SNNs) works focus on an image classifica...
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01/23/2022
Neural Architecture Search for Spiking Neural Networks
Spiking Neural Networks (SNNs) have gained huge attention as a potential...
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06/11/2021
Federated Learning with Spiking Neural Networks
As neural networks get widespread adoption in resource-constrained embed...
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04/07/2021
PrivateSNN: Fully Privacy-Preserving Spiking Neural Networks
How can we bring both privacy and energy-efficiency to a neural system o...
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01/12/2021