Jaouad Mourtada

Statistics and Probability · 2017–2019

A researcher in the Science corpus: 2 papers; trusts 46 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Statistics and Probability — 36 citations into it
• Artificial Intelligence — 17 citations into it
• Statistical Learning Theory — 13 citations into it
• Applied Mathematics — 11 citations into it
• Management Science and Operations Research — 9 citations into it
• Mathematical Physics — 8 citations into it
• Computational Mechanics — 7 citations into it
• Discrete Mathematics and Combinatorics — 5 citations into it

Whom Jaouad Mourtada trusts overall

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

1. David A. McAllester
2. Mark Rudelson
3. Shahar Mendelson
4. Roman Vershynin
5. Terence Tao
6. Olivier Catoni
7. Vladimir Koltchinskii
8. Nicolò Cesa-Bianchi
9. Noureddine El Karoui
10. Alexandre B. Tsybakov

Who trusts Jaouad Mourtada overall

1. Yawei Zhao

Papers from Jaouad Mourtada's perspective

Ordered by how strongly the researchers Jaouad Mourtada 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. Regression Shrinkage and Selection via the Lasso
3. ImageNet classification with deep convolutional neural networks
4. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. Learning Multiple Layers of Features from Tiny Images
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. Attention is All you Need (Neural Information Processing Systems)
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Exact minimax risk for linear least squares, and the lower tail of sample covariance matrices (2019) — 60 citations
• Efficient tracking of a growing number of experts (2017) — 25 citations