Yinwei Dai

Artificial Intelligence · 2021

A researcher in the Science corpus: 2 papers; trusts 7 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 63 citations into it
• Federated & Distributed Learning — 26 citations into it
• Computer Vision and Pattern Recognition — 24 citations into it

Whom Yinwei Dai trusts overall

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

1. Kaiming He
2. Ziteng Sun
3. Mingqing Chen
4. Mark Sandler
5. Peter Kairouz
6. Hongyi Wang
7. H. Brendan McMahan
8. Alex Krizhevsky
9. Timothy Yang
10. Geoffrey E. Hinton

Papers from Yinwei Dai's perspective

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

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

Their papers

• FedScale: Benchmarking Model and System Performance of Federated Learning at Scale (2021) — 302 citations
• FedScale: Benchmarking Model and System Performance of Federated Learning (2021) — 79 citations