Yi Lin

70 papers receiving 8.2k citations

Hit Papers

Model selection and estimation in the Gaussian graphical model 2007 · 952 citations
9520+7+14Years since publication10002.0k3.0k4.0k

Peers

Yi Lin
Comparison fields: 5 of 201
  • Statistics and Probability 2.9k
  • Computational Mathematics 54
  • Artificial Intelligence 2.8k
  • Computer Vision and Pattern Recognition 1.6k
  • Computational Mechanics 1.6k
Replace Ji Zhu with:
Ji Zhu United States
Saharon Rosset Israel
J. S. Marron United States
Ming Yuan United States
Peter L. Bartlett United States
B. W. Silverman United Kingdom
Mark Girolami United Kingdom
Peter Hall Australia
Massimiliano Pontil United Kingdom
Yi Lin relative to Ji Zhu United States Ji Zhu's profile →
Citations per field
00.5×1.5×1.8×
Ji Zhu · 1×
Citations per year

Countries citing papers authored by Yi Lin

Since Specialization
Citations

This map shows the geographic impact of Yi Lin's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Yi Lin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yi Lin more than expected).

Fields of papers citing papers by Yi Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yi Lin. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Yi Lin. The network helps show where Yi Lin may publish in the future.

Co-authors

The 25 scholars most cited alongside Yi Lin, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Yi Lin Line = papers co-authored together Yi Lin links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 75 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Model Selection and Estimation in Regression with Grouped Variables
Hit paper breakdown →
20054545
2
Model selection and estimation in the Gaussian graphical model
Hit paper breakdown →
2007952
3
Multicategory Support Vector Machines
Hit paper breakdown →
2004477
4 2006364
5 2006307
6 2002259
7 2007179
8 2002177
9
A NOTE ON THE LASSO AND RELATED PROCEDURES IN MODEL SELECTION
2006159
10 2020144
11 2004124
12
On the Support Vector Machine
2003121
13 2005118
14 200078
15 201860
16 200754
17 200449
18 202045
19
Prediction cubes
200535
20 201631

About Yi Lin

Yi Lin is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Statistics and Probability, Media Technology and Global and Planetary Change, having authored 75 papers that have together received 8.7k indexed citations. Recurring topics across this work include Statistical Methods and Inference (15 papers), Land Use and Ecosystem Services (11 papers), Remote-Sensing Image Classification (11 papers), Advanced Statistical Methods and Models (10 papers), Remote Sensing and Land Use (10 papers), Face and Expression Recognition (7 papers), Control Systems and Identification (7 papers) and Remote Sensing in Agriculture (4 papers). The work is most often cited by research in Statistics and Probability (2.9k citations), Computational Mathematics (54 citations), Artificial Intelligence (2.8k citations), Computer Vision and Pattern Recognition (1.6k citations) and Computational Mechanics (1.6k citations). Yi Lin has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Ming Yuan, Grace Wahba, Yoonkyung Lee, Hao Helen Zhang, Yongho Jeon, Chenlei Leng, C.Y. Jim, Jinsong Deng, Jie Yu and Zifeng Wang. Their work appears in journals such as International Journal of Applied Earth Observation and Geoinformation, Journal of the American Statistical Association, Remote Sensing, Statistica Sinica and Machine Learning.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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