split-learning

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)

Split Learning Simulation Framework for LLMs

reveal the vulnerabilities of SplitNN

Numerical Evaluation and Implementation of paper: Workflow Optimization for paper Parallel Split Learning (IEEE INFOCOM 2024).

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

Enhancing Efficiency in Multidevice Federated Learning through Data Selection

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

Simple Split Learning setup. Proof of Concept & testbed

Federated Split Learning via Smashed Activation Gradient Estimation

Fine-tuning multimodal models using Parallel Split Learning

testing adhocSL

Split learning framework for PyTorch — partition a model across devices and train end-to-end without any single node holding the full model.

Coding tutorial for Split Learning

AutoEncoder-Compressed Parallel Split Learning for Pre-trained Model Fine-Tuning

Federated LLM

Code of the paper GRAMSSAT: An Efficient Label Inference Attack against Two-party Split Learning based on Gradient Matching and Semi-supervised Learning.

B.Sc. dissertation: slot-attention conditional entropy regularisation against model inversion in split learning; +29.8% attack reconstruction MSE for a 0.84-point accuracy cost on FaceScrub.

Measuring image and label leakage in split federated learning (CIFAR-10, ResNet18)