Akhil Mathur

Artificial Intelligence · 2020

A researcher in the Science corpus: 2 papers; trusts 7 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 53 citations into it
• Federated & Distributed Learning — 24 citations into it
• Optimization & Training — 12 citations into it
• Evaluation & Benchmarks — 9 citations into it
• Signal Processing — 8 citations into it

Whom Akhil Mathur trusts overall

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

1. H. Brendan McMahan
2. Tian Li

Papers from Akhil Mathur's perspective

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

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

Their papers

• Flower: A Friendly Federated Learning Research Framework (2020) — 1,331 citations
• A first look into the carbon footprint of federated learning (2020) — 122 citations