Hongwei Li

Artificial Intelligence · IEEE Transactions on Industrial Informatics · 2009–2021

A researcher in the Science corpus: 7 papers; trusts 24 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 85 citations into it; #23,560 of 35,345 by trust here, #10,319 by citations
• Privacy & Security — 36 citations into it
• Safety, Robustness & Interpretability — 20 citations into it
• Computational Theory and Mathematics — 18 citations into it
• Information Systems — 11 citations into it
• Computer Networks and Communications — 8 citations into it
• Optimization & Training — 8 citations into it
• Health Informatics — 5 citations into it

Whom Hongwei Li trusts overall

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

1. Matthew D. Zeiler
2. Reza Shokri
3. Pascal Paillier
4. Ning Qian
5. L. Eon Bottou
6. Cynthia Dwork
7. El Mahdi El Mhamdi
8. Dan Boneh
9. Keith Bonawitz
10. Alex Krizhevsky

Who trusts Hongwei Li overall

1. Xuefei Yin
2. Meng Hao
3. Yanming Zhu
4. Li Li
5. Jiankun Hu
6. Ali Dehghantanha

Papers from Hongwei Li's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Learning Multiple Layers of Features from Tiny Images
6. ImageNet: A large-scale hierarchical image database
7. Long Short-Term Memory
8. Attention is All you Need (Neural Information Processing Systems)
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Secure Multi-Party Computation: Theory, practice and applications (2019) — 436 citations
• Privacy-Enhanced Federated Learning Against Poisoning Adversaries (2021) — 314 citations
• Efficient and Privacy-Enhanced Federated Learning for Industrial Artificial Intelligence (2020) — 418 citations
• VerifyNet: Secure and Verifiable Federated Learning (2020) — 743 citations
• Towards Efficient and Privacy-Preserving Federated Deep Learning (2019) — 200 citations
• Identity-Based Authentication for Cloud Computing (2009) — 355 citations
• Ieee Transactions on Parallel and Distributed Systems Eppdr: an Efficient Privacy-preserving Demand Response Scheme with Adaptive Key Evolution in Smart Grid