A curated repository for various papers in the domain of split learning.
Split learning for health: Distributed deep learning without sharing raw patient data
SplitFed: When Federated Learning Meets Split Learning
Advances and Open Problems in Federated Learning
Comparison of Privacy-Preserving Distributed Deep Learning Methods in Healthcare
SplitEasy: A Practical Approach for Training ML models on Mobile Devices in a split second
FedSL: Federated Split Learning on Distributed Sequential Data in Recurrent Neural Networks
Multiple Classification with Split Learning
Distributed Heteromodal Split Learning for Vision Aided mmWave Received Power Prediction
SplitFed: When Federated Learning Meets Split Learning
End-to-End Evaluation of Federated Learning and Split Learning for Internet of Things
Can We Use Split Learning on 1D CNN Models for Privacy Preserving Training?
Communication-Efficient Multimodal Split Learning for mmWave Received Power Prediction
Split Learning for collaborative deep learning in healthcare
ExpertMatcher: Automating ML Model Selection for Clients using Hidden Representations
Detailed comparison of communication efficiency of split learning and federated learning
No Peek: A Survey of private distributed deep learning
Interpretable Complex-Valued Neural Networks for Privacy Protection
Mitigating_Information_Leakage_in_Image_Representations_A_Maximum_Entropy_Approach
NoPeek: Information leakage reduction to share activations in distributed deep learning
PRIVATE SPLIT INFERENCE OF DEEP NETWORKS
DISCO: Dynamic and Invariant Sensitive Channel Obfuscation for deep neural networks