Yang Hua

Computer Vision and Pattern Recognition · with Guan · 2022

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

Subfields

• Computer Vision and Pattern Recognition — 8 citations into it

Whom Yang Hua trusts overall

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

1. Alex Krizhevsky
2. Yann LeCun
3. Kaiming He
4. Geoffrey E. Hinton
5. Yoshua Bengio
6. L. Eon Bottou
7. Diederik P. Kingma
8. Junbo Jake Zhao
9. Ilya Sutskever
10. Tian Li

Papers from Yang Hua's perspective

Ordered by how strongly the researchers Yang Hua 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. Gradient-based learning applied to document recognition
3. ImageNet classification with deep convolutional neural networks
4. Learning Multiple Layers of Features from Tiny Images
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
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

• FedALA: Adaptive Local Aggregation for Personalized Federated Learning (2022) — 483 citations