split-learning

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

SRDS 2020: End-to-End Evaluation of Federated Learning and Split Learning for Internet of Things

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

Official Repository for ResSFL (accepted by CVPR '22)

Source codes of paper "Can We Use Split Learning on 1D CNN for Privacy Preserving Training?"

Comparison b/w Federated Learning & Split Learning for credit card fraud detection dataset using Pytorch

Enhancing Efficiency in Multidevice Federated Learning through Data Selection

Framework that supports pipeline federated split learning with multiple hops.

Supplementary code for the paper "SplitGuard: Detecting and MitigatingTraining-Hijacking Attacks in Split Learning"

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

Federated Split Learning via Smashed Activation Gradient Estimation

Fine-tuning multimodal models using Parallel Split Learning

Split learning for privacy-preserving healthcare, and threats and defensive techniques for decentralized learning. (with Prof. Vinay Chamola)

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