Xiaoming Huang

Artificial Intelligence · with Chen · 2021

A researcher in the Science corpus: 1 paper; trusts 5 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 26 citations into it
• Privacy & Security — 10 citations into it
• Safety, Robustness & Interpretability — 10 citations into it
• Optimization & Training — 5 citations into it

Whom Xiaoming Huang trusts overall

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

1. Matthew D. Zeiler
2. Pascal Paillier
3. Ning Qian

Papers from Xiaoming Huang's perspective

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

1. Deep Learning with Differential Privacy
2. Privacy-preserving deep learning
3. Practical Secure Aggregation for Privacy-Preserving Machine Learning
4. Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates
5. Machine Learning with Adversaries: Byzantine Tolerant Gradient Descent
6. Generalized Byzantine-tolerant SGD
7. Poisoning Attacks against Support Vector Machines
8. ADADELTA: An Adaptive Learning Rate Method
9. SecureML: A System for Scalable Privacy-Preserving Machine Learning
10. ImageNet classification with deep convolutional neural networks

Their papers

• Privacy-Enhanced Federated Learning Against Poisoning Adversaries (2021) — 314 citations