Official code for "EC-SNN: Splitting Deep Spiking Neural Networks on Edge Devices" (IJCAI2024)
-
Updated
May 7, 2024 - Python
Official code for "EC-SNN: Splitting Deep Spiking Neural Networks on Edge Devices" (IJCAI2024)
Code and data accompanying the DP-FSL paper
Comparison of distributed machine learning techniques applied to openly available datasets
CycleSL: Server-Client Cyclical Update Driven Scalable Split Learning
Simple Split Learning setup. Proof of Concept & testbed
Split learning for privacy-preserving healthcare, and threats and defensive techniques for decentralized learning. (with Prof. Vinay Chamola)
testing adhocSL
Enhancing Efficiency in Multidevice Federated Learning through Data Selection
Supplementary code for the paper "SplitGuard: Detecting and MitigatingTraining-Hijacking Attacks in Split Learning"
Framework that supports pipeline federated split learning with multiple hops.
Comparison b/w Federated Learning & Split Learning for credit card fraud detection dataset using Pytorch
Official Repository for ResSFL (accepted by CVPR '22)
Source codes of paper "Can We Use Split Learning on 1D CNN for Privacy Preserving Training?"
reveal the vulnerabilities of SplitNN
C3-SL: Circular Convolution-Based Batch-Wise Compression for Communication-Efficient Split Learning (IEEE MLSP 2022)
SRDS 2020: End-to-End Evaluation of Federated Learning and Split Learning for Internet of Things
A unified framework for privacy-preserving data analysis and machine learning
Add a description, image, and links to the split-learning topic page so that developers can more easily learn about it.
To associate your repository with the split-learning topic, visit your repo's landing page and select "manage topics."