Arsalan Sharifnassab

Artificial Intelligence · 2019

A researcher in the Science corpus: 3 papers; trusts 22 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 25 citations into it; #26,084 of 35,345 by trust here, #32,362 by citations
• Optimization & Training — 14 citations into it
• Statistics and Probability — 9 citations into it
• Statistical Learning Theory — 8 citations into it
• Computer Networks and Communications — 7 citations into it; #8,932 of 9,886 by trust here, #9,518 by citations
• Management Science and Operations Research — 7 citations into it
• Computational Mechanics — 5 citations into it
• Information Theory — 5 citations into it

Whom Arsalan Sharifnassab trusts overall

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

1. Saber Salehkaleybar
2. Yuchen Zhang
3. Michael I. Jordan
4. John C. Duchi
5. A. Garg
6. Mark Braverman
7. Jason D. Lee
8. Martin J. Wainwright
9. Jakub Konecný
10. Tengyu Ma

Who trusts Arsalan Sharifnassab overall

1. Saber Salehkaleybar
2. S. J. Golestani
3. Yanlin Zhou

Papers from Arsalan Sharifnassab's perspective

Ordered by how strongly the researchers Arsalan Sharifnassab 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Learning Multiple Layers of Features from Tiny Images
7. ImageNet: A large-scale hierarchical image database
8. Attention is All you Need (Neural Information Processing Systems)
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Order Optimal One-Shot Distributed Learning (2019) — 10 citations
• Theoretical Limits of One-Shot Distributed Learning (2019)
• One-Shot Federated Learning: Theoretical Limits and Algorithms to Achieve Them (2019) — 40 citations