Serena Wang

Artificial Intelligence · 2018–2020

A researcher in the Science corpus: 5 papers; trusts 27 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 63 citations into it; #29,511 of 35,345 by trust here, #13,163 by citations
• Safety Research — 41 citations into it; #5,667 of 5,829 by trust here, #1,499 by citations
• Safety, Robustness & Interpretability — 32 citations into it
• AI Ethics, Fairness & Society — 24 citations into it
• Optimization & Training — 20 citations into it
• Management Science and Operations Research — 13 citations into it
• Computational Theory and Mathematics — 8 citations into it
• Economics and Econometrics — 6 citations into it

Whom Serena Wang trusts overall

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

1. John C. Duchi
2. Andrew Cotter
3. Moritz Hardt
4. David A. Edwards
5. Alekh Agarwal
6. Gabriel Goh
7. Blake E. Woodworth
8. Harikrishna Narasimhan
9. Maya R. Gupta
10. Nati Srebro

Who trusts Serena Wang overall

1. Heinrich Jiang
2. Umang Bhatt
3. Yifan Wang

Papers from Serena Wang's perspective

Ordered by how strongly the researchers Serena Wang 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. Learning Multiple Layers of Features from Tiny Images
6. ImageNet: A large-scale hierarchical image database
7. Attention is All you Need (Neural Information Processing Systems)
8. Long Short-Term Memory
9. Equality of Opportunity in Supervised Learning
10. Adaptive Subgradient Methods for Online Learning and Stochastic Optimization

Their papers

• Optimization with Non-Differentiable Constraints with Applications to Fairness, Recall, Churn, and Other Goals (2018) — 191 citations
• Training Well-Generalizing Classifiers for Fairness Metrics and Other Data-Dependent Constraints (2018) — 119 citations
• Proxy Fairness (2018) — 77 citations
• Robust Optimization for Fairness with Noisy Protected Groups (2020) — 129 citations
• Pairwise Fairness for Ranking and Regression (2019) — 130 citations