A. Genkin
Artificial Intelligence · 2007–2016
A researcher in the Science corpus: 3 papers; trusts 54 researchers and is trusted by 36 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 35 citations into it; #6,381 of 35,345 by trust here, #11,072 by citations
- Statistics and Probability — 20 citations into it
- Computational Mechanics — 16 citations into it
- Optimization & Training — 14 citations into it
- Computer Vision and Pattern Recognition — 10 citations into it; #4,880 of 21,575 by trust here, #7,584 by citations
- Control and Systems Engineering — 10 citations into it
- ML Systems & Hardware — 9 citations into it
- Information Systems — 8 citations into it
Whom A. Genkin trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Robert Tibshirani
- Thorsten Joachims
- Eric R. Ziegel
- Jerome H. Friedman
- Tong Zhang
- Trevor J. Hastie
- J. Langford
- Mário A. T. Figueiredo
- Federico Girosi
- Robert Malouf
Who trusts A. Genkin overall
- Ilya Trofimov
- Guo-Xun Yuan
- Lukas Meier
- Jerome H. Friedman
- Mee Young Park
- Huan Li
- Suhrid Balakrishnan
- Trevor J. Hastie
- R. Caruana
- Kwangmoo Koh
Papers from A. Genkin's perspective
Ordered by how strongly the researchers A. Genkin 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)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Regression Shrinkage and Selection via the Lasso
- Learning Multiple Layers of Features from Tiny Images
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- Large-Scale Bayesian Logistic Regression for Text Categorization (2007) — 911 citations
- Distributed Coordinate Descent for L1-regularized Logistic Regression (2014) — 15 citations
- Distributed coordinate descent for generalized linear models with regularization (2016) — 8 citations