Source codes of paper "Can We Use Split Learning on 1D CNN for Privacy Preserving Training?"
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Updated
Feb 28, 2020 - Jupyter Notebook
Source codes of paper "Can We Use Split Learning on 1D CNN for Privacy Preserving Training?"
SRDS 2020: End-to-End Evaluation of Federated Learning and Split Learning for Internet of Things
Comparison b/w Federated Learning & Split Learning for credit card fraud detection dataset using Pytorch
reveal the vulnerabilities of SplitNN
Official Repository for ResSFL (accepted by CVPR '22)
C3-SL: Circular Convolution-Based Batch-Wise Compression for Communication-Efficient Split Learning (IEEE MLSP 2022)
Code and data accompanying the DP-FSL paper
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)
Supplementary code for the paper "SplitGuard: Detecting and MitigatingTraining-Hijacking Attacks in Split Learning"
Comparison of distributed machine learning techniques applied to openly available datasets
testing adhocSL
Enhancing Efficiency in Multidevice Federated Learning through Data Selection
Official code for "EC-SNN: Splitting Deep Spiking Neural Networks on Edge Devices" (IJCAI2024)
Framework that supports pipeline federated split learning with multiple hops.
CycleSL: Server-Client Cyclical Update Driven Scalable Split Learning
A unified framework for privacy-preserving data analysis and machine learning
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