A unified framework for privacy-preserving data analysis and machine learning
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Updated
Nov 13, 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)
Split Learning Simulation Framework for LLMs
reveal the vulnerabilities of SplitNN
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
Code of the paper GRAMSSAT: An Efficient Label Inference Attack against Two-party Split Learning based on Gradient Matching and Semi-supervised Learning.
Code and data accompanying the DP-FSL paper
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