Saurabh Agarwal

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 77 citations into it
• Federated & Distributed Learning — 26 citations into it
• Computer Vision and Pattern Recognition — 16 citations into it
• Optimization & Training — 16 citations into it

Whom Saurabh Agarwal trusts overall

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

1. Alex Krizhevsky
2. Xiaojin Zhu

Papers from Saurabh Agarwal's perspective

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

1. Long Short-Term Memory
2. Learning Multiple Layers of Features from Tiny Images
3. ImageNet: A large-scale hierarchical image database
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. ImageNet classification with deep convolutional neural networks
6. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
7. Gradient-based learning applied to document recognition
8. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
9. Explaining and Harnessing Adversarial Examples
10. Attention is All you Need (Neural Information Processing Systems)

Their papers

• Attack of the Tails: Yes, You Really Can Backdoor Federated Learning (2020) — 829 citations