Ingo Steinwart

4.7k citations
66 papers · 2.5k · h-index 25

Impact in

    • Statistical Methods and Inference
    • Advanced Statistical Methods and Models
    • Machine Learning and Algorithms
    • Neural Networks and Applications
    • Anomaly Detection Techniques and Applications

Papers in

Ingo Steinwart

64 papers receiving 2.4k citations

Peers

Ingo Steinwart
Comparison fields: 5 of 135
  • Statistics and Probability 639
  • Artificial Intelligence 1.3k
  • Computer Vision and Pattern Recognition 641
  • Computational Mechanics 554
  • Mathematical Physics 195
Replace Bharath K. Sriperumbudur with:
Bharath K. Sriperumbudur United States
Vladimir Koltchinskii United States
Yiming Ying United States
Vladimir Spokoiny Germany
Bernard Delyon France
Pascal Massart France
Marco Cuturi France
Andrea Caponnetto Italy
Anatoli Juditsky France
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Citations per field
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Bharath K. Sriperumbudur · 1×
Citations per year

Countries citing papers authored by Ingo Steinwart

Since Specialization
Citations

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

Fields of papers citing papers by Ingo Steinwart

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 22 scholars most cited alongside Ingo Steinwart, 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 Ingo Steinwart Line = papers co-authored together Ingo Steinwart links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 66 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2008310
2
A Classification Framework for Anomaly Detection
2005171
3 2007164
4 2006148
5 2011145
6
Sparseness of support vector machines
2003142
7 2005134
8
Optimal Rates for Regularized Least Squares Regression.
2009106
9 2002105
10 201291
11 200777
12 200875
13 200370
14 200758
15
How SVMs can estimate quantiles and the median
200748
16
QP Algorithms with Guaranteed Accuracy and Run Time for Support Vector Machines
200645
17
Sparseness of Support Vector Machines---Some Asymptotically Sharp Bounds
200343
18
Fast Learning from Non-i.i.d. Observations
200937
19
Training SVMs without offset
200936
20 200335

About Ingo Steinwart

Ingo Steinwart is a scholar working on Artificial Intelligence, Statistics and Probability, Computer Vision and Pattern Recognition, Control and Systems Engineering and Computational Mechanics, having authored 66 papers that have together received 2.5k indexed citations. Recurring topics across this work include Statistical Methods and Inference (18 papers), Face and Expression Recognition (14 papers), Sparse and Compressive Sensing Techniques (14 papers), Control Systems and Identification (11 papers), Machine Learning and Algorithms (8 papers), Advanced Statistical Methods and Models (8 papers), Neural Networks and Applications (7 papers) and Fault Detection and Control Systems (7 papers). The work is most often cited by research in Statistics and Probability (639 citations), Artificial Intelligence (1.3k citations), Computer Vision and Pattern Recognition (641 citations), Computational Mechanics (554 citations) and Mathematical Physics (195 citations). Ingo Steinwart has collaborated with scholars based in United States, Germany and Belgium. Frequent co-authors include Andreas Christmann, Clint Scovel, Don Hush, D. Hush, Viktor Zaverkin, Johannes Kästner, Patrick J. Kelly, Arnout Van Messem, Muhammad Shoaib Farooq and Simon Fischer. Their work appears in journals such as The Annals of Statistics, Journal of Machine Learning Research, Journal of Complexity, Constructive Approximation 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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