A unified framework for privacy-preserving data analysis and machine learning
-
Updated
Jul 8, 2025 - Python
A unified framework for privacy-preserving data analysis and machine learning
C3-SL: Circular Convolution-Based Batch-Wise Compression for Communication-Efficient Split Learning (IEEE MLSP 2022)
reveal the vulnerabilities of SplitNN
Split Learning Simulation Framework for LLMs
Enhancing Efficiency in Multidevice Federated Learning through Data Selection
Official code of the paper "A Stealthy Wrongdoer: Feature-Oriented Reconstruction Attack against Split Learning".
Official code for "EC-SNN: Splitting Deep Spiking Neural Networks on Edge Devices" (IJCAI2024)
Simple Split Learning setup. Proof of Concept & testbed
testing adhocSL
Federated Split Learning via Smashed Activation Gradient Estimation
Code of the paper GRAMSSAT: An Efficient Label Inference Attack against Two-party Split Learning based on Gradient Matching and Semi-supervised Learning.
CycleSL: Server-Client Cyclical Update Driven Scalable Split Learning
Code and data accompanying the DP-FSL paper
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."