Amir-Reza Asadi

Artificial Intelligence · 2018

A researcher in the Science corpus: 1 paper; trusts 7 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 9 citations into it
• Statistics and Probability — 8 citations into it
• Statistical Learning Theory — 5 citations into it

Whom Amir-Reza Asadi trusts overall

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

1. Michel Talagrand
2. Roman Vershynin
3. Omiros Papaspiliopoulos
4. Ramon van Handel
5. Olivier Bousquet
6. Peter L. Bartlett
7. David A. McAllester
8. Evarist Gin'e
9. Vladimir Koltchinskii
10. Daniel Russo

Who trusts Amir-Reza Asadi overall

1. Pierre Alquier

Papers from Amir-Reza Asadi's perspective

Ordered by how strongly the researchers Amir-Reza Asadi trusts endorse each paper. Same corpus, a different order for every researcher.

1. Understanding deep learning requires rethinking generalization
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Stability and Generalization
4. ImageNet classification with deep convolutional neural networks
5. Learning Multiple Layers of Features from Tiny Images
6. Gradient-based learning applied to document recognition
7. Attention is All you Need (Neural Information Processing Systems)
8. Long Short-Term Memory
9. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Chaining Mutual Information and Tightening Generalization Bounds (2018) — 147 citations