Shinto Eguchi

Statistics and Probability · 2001–2009

A researcher in the Science corpus: 10 papers; trusts 42 researchers and is trusted by 10 researchers here, as inferred from the citation graph.

Subfields

• Statistics and Probability — 48 citations into it; #3,264 of 12,932 by trust here, #3,102 by citations
• Artificial Intelligence — 21 citations into it
• Optimization & Training — 8 citations into it
• Probabilistic & Bayesian Methods — 8 citations into it
• Statistical Learning Theory — 7 citations into it

Whom Shinto Eguchi trusts overall

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

1. Vladimir Naumovich Vapni
2. Calyampudi R. Rao
3. Jerome H. Friedman
4. Robert E. Schapire
5. M. Stone
6. R. Fisher
7. Shun-ichi Amari
8. Trevor J. Hastie
9. Eric R. Ziegel
10. J. Copas

Who trusts Shinto Eguchi overall

1. Paul R. Rosenbaum
2. Shun-ichi Amari
3. Andrzej S. Cichocki
4. J. Copas
5. Dylan S. Small
6. Qiang Liu

Papers from Shinto Eguchi's perspective

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

1. The Nature of Statistical Learning Theory
2. Regression Shrinkage and Selection via the Lasso
3. Generalized Linear Models
4. Special Invited Paper-Additive logistic regression: A statistical view of boosting
5. A decision-theoretic generalization of on-line learning and an application to boosting
6. The Strength of Weak Learnability
7. Gradient-based learning applied to document recognition
8. ImageNet classification with deep convolutional neural networks
9. The Elements of Statistical Learning: Data Mining, Inference, and Prediction
10. UCI Repository of machine learning databases

Their papers

• Importance Sampling Via the Estimated Sampler (2007) — 40 citations
• Local sensitivity approximations for selectivity bias (2001) — 101 citations
• Robust parameter estimation with a small bias against heavy contamination (2008) — 308 citations
• A class of logistic‐type discriminant functions (2002) — 88 citations
• A paradox concerning nuisance parameters and projected estimating functions (2004) — 97 citations
• Robust estimation in the normal mixture model (2006) — 87 citations
• Information Divergence Geometry and the Application to Statistical Machine Learning (2009) — 22 citations
• Robust Boosting Algorithm Against Mislabeling in Multiclass Problems (2008) — 26 citations
• Interpreting Kullback-Leibler divergence with the Neyman-Pearson lemma (2006) — 187 citations
• Local model uncertainty and incomplete‐data bias (with discussion) (2005) — 51 citations