Yuanhao Xiong

Control and Systems Engineering · 2019–2020

A researcher in the Science corpus: 2 papers; trusts 16 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Control and Systems Engineering — 10 citations into it
• Optimization & Training — 10 citations into it; #1,922 of 2,601 by trust here, #1,419 by citations
• Artificial Intelligence — 9 citations into it; #23,298 of 35,345 by trust here, #15,542 by citations
• Building and Construction — 8 citations into it
• Computer Vision and Pattern Recognition — 7 citations into it
• Transportation — 6 citations into it

Whom Yuanhao Xiong trusts overall

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

1. Alex Krizhevsky
2. Kaiming He
3. Diederik P. Kingma
4. Yann LeCun
5. Geoffrey E. Hinton
6. Sepp Hochreiter
7. Yoshua Bengio
8. John C. Duchi
9. Jimmy Ba
10. J. Urgen Schmidhuber

Who trusts Yuanhao Xiong overall

1. Anas Barakat
2. Sharan Vaswani
3. Yuanzhi Li
4. Cyrille W. Combettes
5. Mengtian Li
6. Nicolas Loizou
7. Pedro H. P. Savarese
8. Yan Luo

Papers from Yuanhao Xiong's perspective

Ordered by how strongly the researchers Yuanhao Xiong 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. Gradient-based learning applied to document 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. Attention is All you Need (Neural Information Processing Systems)
8. ImageNet: A large-scale hierarchical image database
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

• Adaptive Gradient Methods with Dynamic Bound of Learning Rate (2019) — 693 citations
• Toward A Thousand Lights: Decentralized Deep Reinforcement Learning for Large-Scale Traffic Signal Control (2020) — 480 citations