Jinshuo Dong
Artificial Intelligence · 2019–2021
A researcher in the Science corpus: 3 papers; trusts 17 researchers and is trusted by 4 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 56 citations into it; #23,842 of 35,345 by trust here, #18,586 by citations
- Privacy & Security — 37 citations into it
- Management Science and Operations Research — 10 citations into it
- Computer Science Applications — 9 citations into it
- Safety, Robustness & Interpretability — 9 citations into it
- Sociology and Political Science — 7 citations into it
Whom Jinshuo Dong trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Cynthia Dwork
- John M. Abowd
- Arthur U. Asuncion
- Adam D. Smith
- Bolin Ding
- John C. Duchi
- Arvind Narayanan
- Mark Bun
- Raef Bassily
- Vitaly Shmatikov
Who trusts Jinshuo Dong overall
- Fatemehsadat Mirshghallah
- Xuechen Li
- Borja Balle
- Ishika Singh
- Yingxue Zhou
- Florian Tramèr
- Mohammadkazem Taram
- Gilles Barthe
- Haoyi Zhou
- Nicolas Papernot
Papers from Jinshuo Dong's perspective
Ordered by how strongly the researchers Jinshuo Dong trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Gradient-based learning applied to document recognition
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Learning Multiple Layers of Features from Tiny Images
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Christine P. Chai's contribution to the Discussion of ‘Gaussian Differential Privacy’ by Dong et al. (2021) — 206 citations
- Deep Learning with Gaussian Differential Privacy (2019) — 250 citations
- Gaussian Di ↵ erential Privacy (2019)