Yi Wu

223 papers receiving 3.1k citations

Yi Wu's Hit Papers

Joint Embedding Learning and Sparse Regression: A Framework for Unsupervised Feature Selection 2013 · 429 citations
4290+4+8Years since publication100200300400

Peers

Yi Wu
Comparison fields: 5 of 133
  • Computer Vision and Pattern Recognition 1.1k
  • Statistics and Probability 323
  • Management Science and Operations Research 399
  • Media Technology 267
  • Computer Networks and Communications 444
Replace Imre J. Rudas with:
Imre J. Rudas Hungary
Ganapati Panda India
Mahesan Niranjan United Kingdom
Sy‐Yen Kuo Taiwan
Nojun Kwak South Korea
Jean-Yves Audibert France
Mónica F. Bugallo United States
Ali Rahimi United States
Antonio Vicino Italy
Yi Wu relative to Imre J. Rudas Hungary Imre J. Rudas's profile →
Citations per field
00.5×3.3×
Imre J. Rudas · 1×
Citations per year

Countries citing papers authored by Yi Wu

Since Specialization
Citations

This map shows the geographic impact of Yi Wu'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 Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yi Wu more than expected).

Fields of papers citing papers by Yi Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yi Wu. 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 Wu. The network helps show where Yi Wu may publish in the future.

Co-authors

The 25 scholars most cited alongside Yi Wu, 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 Wu Line = papers co-authored together Yi Wu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 272 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Joint Embedding Learning and Sparse Regression: A Framework for Unsupervised Feature Selection
Hit paper breakdown →
2013429
2 2017178
3 2020177
4 2018149
5 202184
6 201167
7 202361
8 201458
9 201956
10 202052
11 201951
12 198951
13 200749
14 202248
15 201243
16 200042
17 201737
18 202036
19 202034
20 202233

About Yi Wu

Yi Wu is a scholar working on Electrical and Electronic Engineering, Management Science and Operations Research, Statistics and Probability, Computer Networks and Communications and Computer Vision and Pattern Recognition, having authored 272 papers that have together received 3.3k indexed citations. Recurring topics across this work include Probability and Risk Models (74 papers), Advanced Wireless Communication Technologies (25 papers), Optical Wireless Communication Technologies (25 papers), Financial Risk and Volatility Modeling (21 papers), Statistical Distribution Estimation and Applications (20 papers), Bayesian Methods and Mixture Models (19 papers), Stochastic processes and statistical mechanics (18 papers) and Random Matrices and Applications (18 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.1k citations), Statistics and Probability (323 citations), Management Science and Operations Research (399 citations), Media Technology (267 citations) and Computer Networks and Communications (444 citations). Yi Wu has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Xuejun Wang, Feiping Nie, Dongyun Yi, Chenping Hou, Xuelong Li, Zheng Yang, Zhiguo Ding, Pingzhi Fan, Shuhe Hu and Sijing Cai. Their work appears in journals such as IEEE Transactions on Vehicular Technology, Statistical Papers, Revista de la Real Academia de Ciencias Exactas Físicas y Naturales Serie A Matemáticas, Sensors and Journal of Statistical Computation and Simulation.

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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