Toshiki Sato

Statistics and Probability · 2015–2016

A researcher in the Science corpus: 2 papers; trusts 7 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Statistics and Probability — 9 citations into it; #10,813 of 12,932 by trust here, #10,855 by citations
• Artificial Intelligence — 5 citations into it

Whom Toshiki Sato trusts overall

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

1. Hirotugu Akaike
2. Colin L. Mallows
3. Isabelle M Guyon
4. Daniel McFadden
5. Avrim Blum
6. Alper Ünler
7. Kwangmoo Koh
8. Su-In Lee
9. Andre´ Elisseeff
10. Pat Langley

Who trusts Toshiki Sato overall

1. Berk Ustun
2. Cynthia Rudin
3. Yuichi Takano
4. Ryuhei Miyashiro

Papers from Toshiki Sato's perspective

Ordered by how strongly the researchers Toshiki Sato 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. An Introduction to Variable and Feature Selection
6. Estimating the Dimension of a Model
7. ImageNet: A large-scale hierarchical image database
8. Regression Shrinkage and Selection via the Lasso
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Feature subset selection for logistic regression via mixed integer optimization (2016) — 58 citations
• Piecewise-Linear Approximation for Feature Subset Selection in a Sequential Logit Model (2015) — 27 citations