Rui Tan

Artificial Intelligence · 2019

A researcher in the Science corpus: 2 papers; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Rui Tan trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

  1. Juan Benet
  2. Cynthia Dwork

Papers from Rui Tan's perspective

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

  1. Calibrating Noise to Sensitivity in Private Data Analysis
  2. Communication-Efficient Learning of Deep Networks from Decentralized Data
  3. Deep Models Under the GAN: Information Leakage from Collaborative Deep Learning (Conference on Computer and Communications Security)
  4. Federated Learning: Strategies for Improving Communication Efficiency
  5. RAPPOR: Randomized Aggregatable Privacy-Preserving Ordinal Response
  6. Exploiting Unintended Feature Leakage in Collaborative Learning
  7. Our Data, Ourselves: Privacy Via Distributed Noise Generation
  8. Adaptive Federated Learning in Resource Constrained Edge Computing Systems
  9. Machine Learning with Adversaries: Byzantine Tolerant Gradient Descent
  10. Comprehensive Privacy Analysis of Deep Learning: Passive and Active White-box Inference Attacks against Centralized and Federated Learning

Their papers