Xiaoyu Cao

Artificial Intelligence · 2017–2022

A researcher in the Science corpus: 5 papers; trusts 221 researchers and is trusted by 14 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 144 citations into it; #10,534 of 35,345 by trust here, #11,327 by citations
• Safety, Robustness & Interpretability — 124 citations into it; #819 of 2,251 by trust here, #1,747 by citations
• Signal Processing — 32 citations into it; #2,197 of 7,572 by trust here, #3,784 by citations
• Computer Networks and Communications — 30 citations into it
• Computer Vision and Pattern Recognition — 28 citations into it
• Privacy & Security — 25 citations into it; #643 of 709 by trust here, #426 by citations
• Federated & Distributed Learning — 20 citations into it; #286 of 319 by trust here, #209 by citations
• Optimization & Training — 16 citations into it

Whom Xiaoyu Cao trusts overall

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

1. Kaiming He
2. Ian J. Goodfellow
3. Diederik P. Kingma
4. Alex Krizhevsky
5. Geoffrey E. Hinton
6. Christian Szegedy
7. Nicolas Papernot
8. Nicholas Carlini
9. Yann LeCun
10. Ilya Sutskever

Who trusts Xiaoyu Cao overall

1. Jinyuan Jia
2. Neil Zhenqiang Gong
3. Jianbo Chen
4. Naveed Akhtar
5. Byeongho Heo
6. Binghui Wang
7. Zaixi Zhang
8. Ahmed Salem
9. Huan Zhang
10. Florian Tramèr

Papers from Xiaoyu Cao's perspective

Ordered by how strongly the researchers Xiaoyu Cao 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Mitigating Evasion Attacks to Deep Neural Networks via Region-based Classification (2017) — 219 citations
• FLDetector: Defending Federated Learning Against Model Poisoning Attacks via Detecting Malicious Clients (2022) — 393 citations
• FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping (2020) — 1,101 citations
• Local Model Poisoning Attacks to Byzantine-Robust Federated Learning (2019) — 1,621 citations
• Mitigating Evasion Attacks to Deep Neural Networks via Region-based Classification (2018)