Quan Qian

Artificial Intelligence · 2021

A researcher in the Science corpus: 1 paper; trusts 19 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 23 citations into it
• Federated & Distributed Learning — 8 citations into it
• Privacy & Security — 7 citations into it

Whom Quan Qian trusts overall

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

1. Shai Halevi
2. Pascal Paillier
3. Reza Shokri
4. Craig Gentry
5. Marten van Dijk
6. Adam Coates
7. Runhua Xu
8. Martín Abadi
9. Nathalie Baracaldo
10. Kewei Cheng

Papers from Quan Qian's perspective

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

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

Their papers

• Privacy Preserving Machine Learning with Homomorphic Encryption and Federated Learning (2021) — 385 citations