Chaobing Song

Artificial Intelligence · 2020–2021

A researcher in the Science corpus: 2 papers; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 38 citations into it
• Optimization & Training — 12 citations into it
• Computational Mechanics — 10 citations into it
• Computational Theory and Mathematics — 9 citations into it
• Mathematical Optimization — 6 citations into it

Whom Chaobing Song trusts overall

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

1. Yurii E. Nesterov
2. Arkadi Nemirovski
3. Yura Malitsky
4. Alexander Rakhlin
5. Zhengyuan Zhou
6. Aswin Kannan
7. Panayotis Mertikopoulos
8. Alfredo Noel Iusem
9. Yu-Guan Hsieh
10. Maher Nouiehed

Who trusts Chaobing Song overall

1. Jelena Diakonikolas
2. Constantinos Daskalakis

Papers from Chaobing Song's perspective

Ordered by how strongly the researchers Chaobing Song 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Learning Multiple Layers of Features from Tiny Images
6. ImageNet: A large-scale hierarchical image database
7. Long Short-Term Memory
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. GENERATIVE ADVERSARIAL NETS
10. Attention is All you Need (Neural Information Processing Systems)

Their papers

• Optimistic Dual Extrapolation for Coherent Non-monotone Variational Inequalities (2021) — 54 citations
• Learning Diverse and Discriminative Representations via the Principle of Maximal Coding Rate Reduction (2020) — 251 citations