A unified framework for privacy-preserving data analysis and machine learning

reveal the vulnerabilities of SplitNN

Split Learning Simulation Framework for LLMs

Enhancing Efficiency in Multidevice Federated Learning through Data Selection

C3-SL: Circular Convolution-Based Batch-Wise Compression for Communication-Efficient Split Learning (IEEE MLSP 2022)

CycleSL: Server-Client Cyclical Update Driven Scalable Split Learning

Code and data accompanying the DP-FSL paper

Official code for "EC-SNN: Splitting Deep Spiking Neural Networks on Edge Devices" (IJCAI2024)

testing adhocSL

Simple Split Learning setup. Proof of Concept & testbed

Official code of the paper "A Stealthy Wrongdoer: Feature-Oriented Reconstruction Attack against Split Learning".