Yang Bao

Artificial Intelligence · 2014–2020

A researcher in the Science corpus: 3 papers; trusts 33 researchers and is trusted by 23 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 30 citations into it; #9,062 of 35,345 by trust here, #18,586 by citations
• Accounting — 22 citations into it
• Information Systems — 14 citations into it; #2,053 of 8,771 by trust here, #4,682 by citations
• Finance — 13 citations into it
• Evaluation & Benchmarks — 6 citations into it
• Sociology and Political Science — 6 citations into it
• Statistics and Probability — 6 citations into it
• Electrical and Electronic Engineering — 5 citations into it

Whom Yang Bao trusts overall

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

1. Feng Li
2. Yehuda Koren
3. David M. Blei
4. Michael I. Jordan
5. Justin Grimmer
6. Ruslan Salakhutdinov
7. Peter J. Rousseeuw
8. Chih-Jen Lin
9. Eric R. Ziegel
10. Robert M. Bell

Who trusts Yang Bao overall

1. Zhiyong Cheng
2. Ruining He
3. Ingrid E. Fisher
4. Tzu-Ting Chiu
5. Chenliang Li
6. Guangneng Hu
7. Hao Wang
8. Lei Zheng
9. Libing Wu
10. Sungyong Seo

Papers from Yang Bao's perspective

Ordered by how strongly the researchers Yang Bao 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. Gradient-based learning applied to document recognition
5. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
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

• TopicMF: Simultaneously Exploiting Ratings and Reviews for Recommendation (2014) — 302 citations
• Simultaneously Discovering and Quantifying Risk Types from Textual Risk Disclosures (2014) — 402 citations
• Detecting Accounting Fraud in Publicly Traded U.S. Firms Using a Machine Learning Approach (2020) — 299 citations