← authors · overview

• FedML: A Research Library and Benchmark for Federated Machine Learning
  2020 · 358 citations
• Split learning for health: Distributed deep learning without sharing raw patient data
  2018 · 179 citations
• No Peek: A Survey of private distributed deep learning
  2018 · 47 citations
• Detailed comparison of communication efficiency of split learning and federated learning
  2019 · 44 citations
• AdaSplit: Adaptive Trade-offs for Resource-constrained Distributed Deep Learning
  2021 · 14 citations
• Server-Side Local Gradient Averaging and Learning Rate Acceleration for Scalable Split Learning
  2021 · 12 citations
• NoPeek: Information leakage reduction to share activations in distributed deep learning
  2020 · 10 citations
• Visual Transformer Meets CutMix for Improved Accuracy, Communication Efficiency, and Data Privacy in Split Learning
  2022 · 4 citations
• Differentially Private CutMix for Split Learning with Vision Transformer
  2022 · 4 citations
• DAVED: Data Acquisition via Experimental Design for Data Markets
  2024 · 1 citations
• Tackling Feature and Sample Heterogeneity in Decentralized Multi-Task Learning: A Sheaf-Theoretic Approach
  2025
• Splintering with distributions: A stochastic decoy scheme for private computation
  2020
• Predicting Survival of Hemodialysis Patients using Federated Learning
  2024