Brian Kriegler

Statistics and Probability · 2005–2010

A researcher in the Science corpus: 2 papers; trusts 11 researchers and is trusted by 8 researchers here, as inferred from the citation graph.

Subfields

• Statistics and Probability — 17 citations into it; #7,889 of 12,932 by trust here, #8,279 by citations
• Artificial Intelligence — 12 citations into it; #21,523 of 35,345 by trust here, #27,551 by citations
• Statistical Learning Theory — 8 citations into it

Whom Brian Kriegler trusts overall

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

1. Jerome H. Friedman
2. Leo Breiman
3. Nicolai Meinshausen
4. Kai Ming Ting
5. Yoav Freund
6. Robert E. Schapire
7. Tong Zhang
8. Bin Yu
9. Peter Buhlmann
10. H. Leeb

Who trusts Brian Kriegler overall

1. Richard A. Berk
2. Anru R. Zhang
3. Lawrence D. Brown
4. Jiaming Zeng
5. Tommaso Cai
6. Benjamin Wilson

Papers from Brian Kriegler's perspective

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

1. Bagging Predictors
2. Greedy function approximation: A gradient boosting machine.
3. Gradient-based learning applied to document recognition
4. ImageNet classification with deep convolutional neural networks
5. Regression Shrinkage and Selection via the Lasso
6. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. A decision-theoretic generalization of on-line learning and an application to boosting
9. The Nature of Statistical Learning Theory
10. Going deeper with convolutions

Their papers

• Forecasting Dangerous Inmate Misconduct: An Application of Ensemble Statistical Procedures (2005) — 91 citations
• Small Area Estimation of the Homeless in Los Angeles: An Application of Cost-Sensitive stochastic Gradient Boosting (2010) — 50 citations