C. Sutton

Artificial Intelligence · 2005

A researcher in the Science corpus: 1 paper; trusts 12 researchers and is trusted by 9 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 7 citations into it; #10,064 of 35,345 by trust here, #25,040 by citations
• Statistical Learning Theory — 6 citations into it
• Statistics and Probability — 6 citations into it

Whom C. Sutton trusts overall

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

1. Leo Breiman
2. J. Ross Quinlan
3. Robert E. Schapire
4. Yoav Freund
5. Wei-Yin Loh
6. Jerome H. Friedman
7. Yu-Shan Shih
8. David Ruppert
9. Jr. Frank E. Harrell
10. Yann LeCun

Who trusts C. Sutton overall

1. Alexey Natekin
2. Julian D. Olden
3. Yufei Xia
4. Alois C. Knoll
5. Joshua J. Lawler
6. Chuanzhe Liu
7. N. LeRoy Poff
8. Yuying Li
9. Jeffrey Scott Evans
10. Antoine Jean-Pierre Tixier

Papers from C. Sutton's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Gradient-based learning applied to document recognition
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. The Strength of Weak Learnability
6. Bagging Predictors
7. The Nature of Statistical Learning Theory
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. Going deeper with convolutions
10. Attention is All you Need (Neural Information Processing Systems)

Their papers

• Classification and Regression Trees, Bagging, and Boosting (2005) — 524 citations