Bing Li

Statistics and Probability · with Cook · 2000–2018

A researcher in the Science corpus: 18 papers; trusts 55 researchers and is trusted by 62 researchers here, as inferred from the citation graph.

Subfields

• Statistics and Probability — 116 citations into it; #632 of 12,932 by trust here, #682 by citations
• Artificial Intelligence — 29 citations into it; #15,598 of 35,345 by trust here, #19,439 by citations
• Representation & Self-Supervised Learning — 21 citations into it
• Management Science and Operations Research — 20 citations into it; #2,075 of 11,946 by trust here, #3,705 by citations
• Statistical Learning Theory — 17 citations into it
• Control and Systems Engineering — 15 citations into it; #761 of 8,257 by trust here, #1,518 by citations
• Computational Mechanics — 14 citations into it
• Analytical Chemistry — 9 citations into it; #229 of 1,254 by trust here, #456 by citations

Whom Bing Li trusts overall

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

1. Ker-Chau Li
2. R. Dennis Cook
3. Xiangrong Yin
4. Efstathia Bura
5. Yingcun Xia
6. James R. Schott
7. Peter M. Bentler
8. Zhishen Ye
9. Shaoli Wang
10. Ronald Christensen

Who trusts Bing Li overall

1. R. Dennis Cook
2. Xiangrong Yin
3. Kenji Fukumizu
4. Wenhui Sheng
5. Wei Luo
6. Yingcun Xia
7. Kofi P. Adragni
8. Chenlei Leng
9. Hansheng Wang
10. Yanyuan Ma

Papers from Bing Li's perspective

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

1. Sliced Inverse Regression for Dimension Reduction
2. Regression Shrinkage and Selection via the Lasso
3. Dimension reduction for conditional mean in regression
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. ImageNet classification with deep convolutional neural networks
6. Gradient-based learning applied to document recognition
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. Graphics for regressions with a binary response
9. Estimating the Dimension of a Model
10. Long Short-Term Memory

Their papers

• Optimal sufficient dimension reduction in regressions with categorical predictors (2002) — 166 citations
• Dimension reduction for conditional mean in regression (2002) — 427 citations
• Contour regression: A general approach to dimension reduction (2005) — 335 citations
• On Directional Regression for Dimension Reduction (2007) — 520 citations
• Dimension reduction for the conditional mean in regressions with categorical predictors (2003) — 93 citations
• Likelihood-Based Sufficient Dimension Reduction (2009) — 169 citations
• Improving generalised estimating equations using quadratic inference functions (2000) — 449 citations
• Successive direction extraction for estimating the central subspace in a multiple-index regression (2008) — 211 citations
• On a Projective Resampling Method for Dimension Reduction With Multivariate Responses (2008) — 107 citations
• Sufficient dimension reduction based on an ensemble of minimum average variance estimators (2011) — 85 citations
• Dimension reduction for nonelliptically distributed predictors (2009) — 121 citations
• Dimension reduction in regression without matrix inversion (2007) — 105 citations
• Sufficient Dimension Reduction: Methods and Applications with R (2018) — 249 citations
• Nonlinear sufficient dimension reduction for functional data (2017) — 81 citations
• Combining eigenvalues and variation of eigenvectors for order determination (2016) — 131 citations
• A general theory for nonlinear sufficient dimension reduction: Formulation and estimation (2013) — 110 citations
• Groupwise Dimension Reduction (2010) — 55 citations
• ENVELOPE MODELS FOR PARSIMONIOUS AND EFFICIENT MULTIVARIATE LINEAR REGRESSION (2010) — 198 citations