Yang Lan

International Journal of Machine Learning and Cybernetics · with Zhang · 2022

A researcher in the Science corpus: 1 paper; trusts 0 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Papers from Yang Lan's perspective

Ordered by how strongly the researchers Yang Lan trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Communication-Efficient Learning of Deep Networks from Decentralized Data
  2. Practical Secure Aggregation for Privacy-Preserving Machine Learning
  3. Client Selection for Federated Learning with Heterogeneous Resources in Mobile Edge
  4. Protocols for secure computations
  5. Federated Learning of Deep Networks using Model Averaging
  6. Differentially Private Federated Learning: A Client Level Perspective
  7. Sharemind: A Framework for Fast Privacy-Preserving Computations
  8. Privacy‐preserving federated learning based on multi‐key homomorphic encryption (International Journal of Intelligent Systems)
  9. A Hybrid BlockChain-Based Identity Authentication Scheme for Multi-WSN (IEEE Transactions on Services Computing)
  10. A Blockchain-Based Decentralized Federated Learning Framework with Committee Consensus (IEEE Network)

Their papers