Robin C. Geyer

Artificial Intelligence · 2017

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 31 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 14 citations into it; #6,564 of 35,345 by trust here, #7,062 by citations

Whom Robin C. Geyer trusts overall

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

1. H. Brendan McMahan
2. Cynthia Dwork
3. Martín Abadi
4. Daniel Ramage
5. Eider Moore
6. Arvind Narayanan
7. Andy Chu
8. Ravid Shwartz-Ziv
9. Vitaly Shmatikov

Who trusts Robin C. Geyer overall

1. Lichao Sun
2. Luping Wang
3. Tribhuvanesh Orekondy
4. Congzheng Song
5. Stephanie L. Hyland
6. Vitaly Shmatikov
7. Eugene Bagdasarian
8. Lingjuan Lyu
9. Praneeth Vepakomma
10. Young Geun Kim

Papers from Robin C. Geyer's perspective

Ordered by how strongly the researchers Robin C. Geyer trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Gradient-based learning applied to document recognition
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Learning Multiple Layers of Features from Tiny Images
5. Long Short-Term Memory
6. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
7. Deep Learning with Differential Privacy
8. ImageNet: A large-scale hierarchical image database
9. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
10. Going deeper with convolutions

Their papers

• Differentially Private Federated Learning: A Client Level Perspective (2017) — 1,680 citations