Yang Yu

Artificial Intelligence · with Hu · 2014–2021

A researcher in the Science corpus: 13 papers; trusts 382 researchers and is trusted by 12 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 320 citations into it; #11,951 of 35,345 by trust here, #8,893 by citations
• Computer Vision and Pattern Recognition — 128 citations into it
• Optimization & Training — 78 citations into it
• Computational Theory and Mathematics — 74 citations into it
• Reinforcement Learning — 58 citations into it; #2,083 of 2,242 by trust here, #1,973 by citations
• Neural Architecture Search & AutoML — 54 citations into it; #243 of 283 by trust here, #145 by citations
• Model Architectures — 46 citations into it
• Management Science and Operations Research — 38 citations into it; #5,666 of 11,946 by trust here, #8,062 by citations

Whom Yang Yu trusts overall

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

1. Yoshua Bengio
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Yann LeCun
5. Vladimir Naumovich Vapni
6. Diederik P. Kingma
7. Ilya Sutskever
8. Kaiming He
9. L. Eon Bottou
10. Ronan Collobert

Who trusts Yang Yu overall

1. Yi-Qi Hu
2. Wang-Zhou Dai
3. Quanming Yao
4. Da-Wei Zhou
5. Zhi-Hua Zhou
6. Tong Yu
7. Wei-Wei Tu
8. Guangyao Chen
9. Qiu-Ling Xu
10. Katikapalli Subramanyam Kalyan

Papers from Yang Yu's perspective

Ordered by how strongly the researchers Yang Yu 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. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Learning Multiple Layers of Features from Tiny Images
10. Going deeper with convolutions

Their papers

• TurboTransformers: an efficient GPU serving system for transformer models (2020) — 180 citations
• Automated Machine Learning: From Principles to Practices (2018) — 264 citations
• Multi-Fidelity Automatic Hyper-Parameter Tuning via Transfer Series Expansion (2019) — 37 citations
• Sequential Classification-Based Optimization for Direct Policy Search (2017) — 51 citations
• Derivative-Free Optimization via Classification (2016) — 96 citations
• QPLEX: Duplex Dueling Multi-Agent Q-Learning (2020) — 633 citations
• Chaotic Local Search-Based Differential Evolution Algorithms for Optimization (2021) — 310 citations
• Parallel Training of Pre-Trained Models via Chunk-Based Dynamic Memory Management (2021) — 48 citations
• Experienced Optimization with Reusable Directional Model for Hyper-Parameter Search (2018) — 13 citations
• On Reinforcement Learning for Full-length Game of StarCraft (2018) — 93 citations
• Taking Human out of Learning Applications: A Survey on Automated Machine Learning (2018) — 216 citations
• Tunneling Neural Perception and Logic Reasoning through Abductive Learning (2018) — 24 citations
• Learning with Augmented Class by Exploiting Unlabeled Data (2014) — 111 citations