Linda Kaufman
- Artificial Intelligence top 1%
- Radiology, Nuclear Medicine and Imaging top 1%
- Computational Theory and Mathematics top 0.5%
- Computer Vision and Pattern Recognition top 2%
- Electrical and Electronic Engineering top 10%
- Co-authors
- Alex SmolaVladimir VapnikHarris DruckerChristopher J. C. BurgesY. VardiL. A. SheppJames R. BunchG. W. Stewart
- Topics
- Matrix Theory and Algorithms (20 papers)Advanced Optimization Algorithms Research (12 papers)Medical Imaging Techniques and Applications (9 papers)
- Journals
- Journal of the American Statistical AssociationThe Science of The Total EnvironmentMathematics of Computation
- Partner nations
- United StatesAustriaDenmark
In The Last Decade
Linda Kaufman
46 papers receiving 5.1k citations
Hit Papers
Peers
Comparison fields: 5 of 199
- Artificial Intelligence 975
- Radiology, Nuclear Medicine and Imaging 929
- Computational Theory and Mathematics 783
- Computer Vision and Pattern Recognition 662
- Electrical and Electronic Engineering 621
Countries citing papers authored by Linda Kaufman
This map shows the geographic impact of Linda Kaufman'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 Linda Kaufman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Linda Kaufman more than expected).
Fields of papers citing papers by Linda Kaufman
This network shows the impact of papers produced by Linda Kaufman. 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 Linda Kaufman. The network helps show where Linda Kaufman may publish in the future.
Co-authorship network of co-authors of Linda Kaufman
This figure shows the co-authorship network connecting the top 25 collaborators of Linda Kaufman. A scholar is included among the top collaborators of Linda Kaufman based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Linda Kaufman. Linda Kaufman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 51 | |
| 2 | 0 | |
| 3 | 16 | |
| 4 | Support Vector Regression Machinesbreakdown → | 3109 |
| 5 | 33 | |
| 6 | 130 | |
| 7 | 11 | |
| 8 | 8 | |
| 9 | 28 | |
| 10 | A Statistical Model for Positron Emission Tomographybreakdown → | 554 |
| 11 | 27 | |
| 12 | 54 | |
| 13 | 11 | |
| 14 | 32 | |
| 15 | 19 | |
| 16 | 234 | |
| 17 | 250 | |
| 18 | 66 | |
| 19 | 175 | |
| 20 | 47 |
About Linda Kaufman
Linda Kaufman is a scholar working on Numerical Analysis, Computational Mathematics and Computational Theory and Mathematics, having authored 49 papers that have together received 5.6k indexed citations. Recurring topics across this work include Matrix Theory and Algorithms (20 papers), Advanced Optimization Algorithms Research (12 papers) and Medical Imaging Techniques and Applications (9 papers). The work is most often cited by research in Numerical Analysis (424 citations), Computational Theory and Mathematics (783 citations) and Computational Mathematics (29 citations). Linda Kaufman has collaborated with scholars based in United States, Austria and Denmark. Frequent co-authors include Alex Smola, Vladimir Vapnik, Harris Drucker, Christopher J. C. Burges, Y. Vardi, L. A. Shepp, James R. Bunch, G. W. Stewart, William B. Gragg and Arnold Neumaier. Their work appears in journals such as Journal of the American Statistical Association, The Science of The Total Environment and Mathematics of Computation.
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.