Shaowei Wang

Artificial Intelligence · with Huang · 2016–2020

A researcher in the Science corpus: 3 papers; trusts 10 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 56 citations into it; #29,766 of 35,345 by trust here, #18,186 by citations
• Privacy & Security — 37 citations into it
• Statistics and Probability — 14 citations into it
• Algorithms & Complexity — 7 citations into it
• Optimization & Training — 7 citations into it

Whom Shaowei Wang trusts overall

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

1. Robert Tibshirani
2. Jeffrey Scott Vitter
3. Cynthia Dwork
4. John C. Duchi
5. Adam D. Smith
6. Peter Kairouz
7. Frank McSherry
8. Weiran Wang
9. Shiva Prasad Kasiviswanathan
10. Konstantinos Chatzikokolakis

Who trusts Shaowei Wang overall

1. Jayadev Acharya
2. Ziteng Sun
3. Vitaly Feldman
4. Tianhao Wang
5. Min Ye
6. Kunal Talwar
7. Huanyu Zhang
8. Alexander Barg

Papers from Shaowei Wang's perspective

Ordered by how strongly the researchers Shaowei 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. Gradient-based learning applied to document recognition
4. GENERATIVE ADVERSARIAL NETS
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Learning Multiple Layers of Features from Tiny Images
7. ImageNet: A large-scale hierarchical image database
8. Long Short-Term Memory
9. Calibrating Noise to Sensitivity in Private Data Analysis
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Local Differential Private Data Aggregation for Discrete Distribution Estimation (2019) — 81 citations
• Private FL-GAN: Differential Privacy Synthetic Data Generation Based on Federated Learning (2020) — 104 citations
• Mutual Information Optimally Local Private Discrete Distribution Estimation (2016) — 100 citations