Ingo Steinwart
- Statistics and Probability top 0.5%
- Statistical Methods and Inference 18
- Advanced Statistical Methods and Models 8
- Artificial Intelligence top 1%
- Machine Learning and Algorithms 8
- Bayesian Methods and Mixture Models 7
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- Face and Expression Recognition 14
- Computational Mechanics top 2%
- Sparse and Compressive Sensing Techniques 14
- Mathematical Physics top 5%
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- Control Systems and Identification 11
- Fault Detection and Control Systems 7
- Co-authors
- Clint ScovelAndreas ChristmannDon HushD. HushJohannes KästnerViktor ZaverkinPatrick J. KellyArnout Van Messem
- Journals
- The Annals of Statistics (5 papers)Journal of Machine Learning Research (5 papers)Journal of Complexity (4 papers)
- Partner nations
- United StatesGermanyBelgium
In The Last Decade
Ingo Steinwart
62 papers receiving 2.0k citations
Peers
Comparison fields: 5 of 124
- Statistics and Probability 609
- Artificial Intelligence 1.1k
- Computer Vision and Pattern Recognition 588
- Computational Mechanics 519
- Mathematical Physics 183
Countries citing papers authored by Ingo Steinwart
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
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-authorship network
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.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Sobolev Norm Learning Rates for Regularized Least-Squares Algorithms | 2020 | 10 |
| 2 | Optimal learning rates for localized SVMs | 2016 | 10 |
| 3 | Elicitation and Identification of Properties | 2014 | 25 |
| 4 | Consistency and Rates for Clustering with DBSCAN | 2012 | 9 |
| 5 | Adaptive Density Level Set Clustering | 2011 | 8 |
| 6 | Universal Kernels on Non-Standard Input Spaces | 2010 | 29 |
| 7 | 2010 | 19 | |
| 8 | Optimal Rates for Regularized Least Squares Regression. | 2009 | 106 |
| 9 | Training SVMs without offset | 2009 | 35 |
| 10 | Sparsity of SVMs that use the epsilon-insensitive loss | 2008 | 9 |
| 11 | Sparsity of SVMs that use the ∊-insensitive loss | 2008 | 1 |
| 12 | 2008 | 74 | |
| 13 | How SVMs can estimate quantiles and the median | 2007 | 48 |
| 14 | QP Algorithms with Guaranteed Accuracy and Run Time for Support Vector Machines | 2006 | 44 |
| 15 | A Classification Framework for Anomaly Detection | 2005 | 171 |
| 16 | Fast Rates to Bayes for Kernel Machines | 2004 | 5 |
| 17 | Sparseness of Support Vector Machines---Some Asymptotically Sharp Bounds | 2003 | 43 |
| 18 | Sparseness of support vector machines | 2003 | 142 |
| 19 | 2001 | 9 | |
| 20 | 2000 | 12 |
About Ingo Steinwart
Ingo Steinwart is a scholar working on Statistics and Probability, Mathematical Physics, Computer Vision and Pattern Recognition, Artificial Intelligence and Numerical Analysis, having authored 65 papers that have together received 2.2k indexed citations. Recurring topics across this work include Statistical Methods and Inference (18 papers), Sparse and Compressive Sensing Techniques (14 papers), Face and Expression Recognition (14 papers), Control Systems and Identification (11 papers), Machine Learning and Algorithms (8 papers), Advanced Statistical Methods and Models (8 papers), Bayesian Methods and Mixture Models (7 papers) and Fault Detection and Control Systems (7 papers). The work is most often cited by research in Statistics and Probability (609 citations), Artificial Intelligence (1.1k citations), Computer Vision and Pattern Recognition (588 citations), Computational Mechanics (519 citations) and Mathematical Physics (183 citations). Ingo Steinwart has collaborated with scholars based in United States, Germany and Belgium. Frequent co-authors include Clint Scovel, Andreas Christmann, Don Hush, D. Hush, Johannes Kästner, Viktor Zaverkin, 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, Machine Learning and Constructive Approximation.
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.