Bing Bai

Artificial Intelligence · 2009–2020

A researcher in the Science corpus: 3 papers; trusts 9 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 34 citations into it; #29,258 of 35,345 by trust here, #21,878 by citations
• Natural Language Processing — 13 citations into it
• Information Systems — 10 citations into it
• Representation & Self-Supervised Learning — 9 citations into it
• Computer Vision and Pattern Recognition — 8 citations into it; #17,991 of 21,575 by trust here, #14,478 by citations
• Information Retrieval & Search — 6 citations into it; #852 of 1,022 by trust here, #663 by citations
• Statistics and Probability — 6 citations into it

Whom Bing Bai trusts overall

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

1. Thorsten Joachims
2. Donald B. Rubin
3. Ruslan Salakhutdinov
4. Geoffrey E. Hinton
5. Silviu Cucerzan
6. Radford M. Neal
7. David M. Blei
8. Michael Collins
9. David Grangier
10. Razvan C. Bunescu

Who trusts Bing Bai overall

1. Florent Perronnin
2. Samuel Humeau
3. Zeynep Akata
4. Stéphane Clinchant
5. Zhengdong Lu
6. José A. Rodríguez-Serrano
7. Kurt Shuster
8. Hang Li
9. Jason Aaron Edward Weston
10. Ledell Yu Wu

Papers from Bing Bai's perspective

Ordered by how strongly the researchers Bing Bai 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. Learning Multiple Layers of Features from Tiny Images
9. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
10. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)

Their papers

• Supervised semantic indexing (2009) — 107 citations
• Demographics Should Not Be the Reason of Toxicity: Mitigating Discrimination in Text Classifications with Instance Weighting (2020) — 81 citations
• Bayesian models for Large-scale Hierarchical Classification (2012) — 50 citations