Alexey Natekin
Artificial Intelligence · 2013
A researcher in the Science corpus: 1 paper; trusts 15 researchers and is trusted by 9 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 12 citations into it; #14,739 of 35,345 by trust here, #19,018 by citations
- Statistics and Probability — 7 citations into it
- Computer Vision and Pattern Recognition — 5 citations into it; #9,505 of 21,575 by trust here, #12,689 by citations
- Optimization & Training — 5 citations into it
Whom Alexey Natekin trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Robert E. Schapire
- Jerome H. Friedman
- Niko Speybroeck
- Xin Yao
- Yifan Hu
- C. Sutton
- Yoav Freund
- Tong Zhang
- Hui Zou
- Trevor J. Hastie
Who trusts Alexey Natekin overall
- Ibomoiye Domor Mienye
- Alexander Rakhlin
- Azal Ahmad Khan
- Y. Raita
- Yanxia Sun
- Omkar Chaudhari
- Alexey A. Shvets
- Aleksei Tiulpin
- T. Goto
- Omer Sagi
Papers from Alexey Natekin's perspective
Ordered by how strongly the researchers Alexey Natekin trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Gradient-based learning applied to document recognition
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Random Forests
- A decision-theoretic generalization of on-line learning and an application to boosting
- Special Invited Paper-Additive logistic regression: A statistical view of boosting
- Regression Shrinkage and Selection via the Lasso
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Going deeper with convolutions
Their papers
- Gradient boosting machines, a tutorial (2013) — 3,482 citations