Benoit Sanchez

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 19 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 17 citations into it
• Scaling & Learning Theory — 15 citations into it
• Statistics and Probability — 12 citations into it
• Computational Mechanics — 9 citations into it
• Optimization & Training — 8 citations into it
• Statistical Learning Theory — 7 citations into it
• Computer Vision and Pattern Recognition — 6 citations into it

Whom Benoit Sanchez trusts overall

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

1. Robert Tibshirani
2. Trevor J. Hastie
3. Jerome H. Friedman
4. E.J. Candes
5. Mikhail Belkin
6. Hui Zou
7. Ali Rahimi
8. B. Recht
9. Scott Shaobing Chen
10. Tengyuan Liang

Papers from Benoit Sanchez's perspective

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

1. Regression Shrinkage and Selection via the Lasso
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. ImageNet classification with deep convolutional neural networks
4. Dropout: a simple way to prevent neural networks from overfitting
5. Gradient-based learning applied to document recognition
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. The Nature of Statistical Learning Theory
8. The Elements of Statistical Learning
9. Understanding deep learning requires rethinking generalization
10. ImageNet: A large-scale hierarchical image database

Their papers

• The Optimal Ridge Penalty for Real-world High-dimensional Data Can Be Zero or Negative due to the Implicit Ridge Regularization (2020) — 20 citations