Ralf Herbrich
Impact in
- Artificial Intelligence top 0.5%
- Machine Learning and Algorithms
- Gaussian Processes and Bayesian Inference
- Neural Networks and Applications
- Machine Learning and Data Classification
- Topic Modeling
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- Face and Expression Recognition
Papers in
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- Machine Learning and Algorithms 21
- Neural Networks and Applications 16
- Machine Learning and Data Classification 14
- Gaussian Processes and Bayesian Inference 9
- Algorithms and Data Compression 5
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- Face and Expression Recognition 10
- Co-authors
- Thore Graepel (36 shared papers)Joaquin Quiñonero Candela (3 shared papers)Neil D. Lawrence (4 shared papers)David Stern (8 shared papers)Matthias Seeger (3 shared papers)Arthur Gretton (5 shared papers)Bernhard Schölkopf (2 shared papers)Ou Jin (1 shared paper)
- Journals
- Journal of Machine Learning Research (2 papers)IEEE Transactions on Information Theory (1 paper)Machine Learning (1 paper)The MIT Press eBooks (1 paper)Infoscience (Ecole Polytechnique Fédérale de Lausanne) (1 paper)
- Partner nations
- United KingdomUnited StatesGermany
In The Last Decade
Ralf Herbrich
66 papers receiving 3.3k citations
Ralf Herbrich's Hit Papers
Peers
Comparison fields: 5 of 155
- Artificial Intelligence 2.1k
- Computer Vision and Pattern Recognition 997
- Information Systems 794
- Signal Processing 358
- Management Science and Operations Research 412
Countries citing papers authored by Ralf Herbrich
This map shows the geographic impact of Ralf Herbrich'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 Ralf Herbrich with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ralf Herbrich more than expected).
Fields of papers citing papers by Ralf Herbrich
This network shows the impact of papers produced by Ralf Herbrich. 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 Ralf Herbrich. The network helps show where Ralf Herbrich may publish in the future.
Co-authors
The 25 scholars most cited alongside Ralf Herbrich, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 69 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Practical Lessons from Predicting Clicks on Ads at Facebook Hit paper breakdown → | 2014 | 519 |
| 2 | 1999 | 322 | |
| 3 | Fast Sparse Gaussian Process Methods: The Informative Vector Machine | 2002 | 319 |
| 4 | 2001 | 299 | |
| 5 | Web-Scale Bayesian Click-Through rate Prediction for Sponsored Search Advertising in Microsoft's Bing Search Engine | 2010 | 266 |
| 6 | Kernel Methods for Measuring Independence | 2005 | 188 |
| 7 | 2009 | 157 | |
| 8 | Generalization Bounds for the Area Under the ROC Curve | 2005 | 146 |
| 9 | Predicting Information Spreading in Twitter | 2010 | 118 |
| 10 | Learning Kernel Classifiers | 2001 | 105 |
| 11 | Classification on Pairwise Proximity Data | 1998 | 97 |
| 12 | The Perceptron Algorithm with Uneven Margins | 2002 | 90 |
| 13 | 2002 | 71 | |
| 14 | TrueSkill Through Time: Revisiting the History of Chess | 2007 | 59 |
| 15 | LEARNING TO FIGHT | 2004 | 52 |
| 16 | Microsoft Cambridge at TREC 2002: Filtering Track. | 2000 | 44 |
| 17 | 2006 | 37 | |
| 18 | 1999 | 37 | |
| 19 | Generalisation Error Bounds for Sparse Linear Classifiers | 2000 | 36 |
| 20 | Learning Preference Relations for Information Retrieval | 1998 | 36 |
About Ralf Herbrich
Ralf Herbrich is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Management Science and Operations Research, Information Systems and Statistical and Nonlinear Physics, having authored 69 papers that have together received 3.6k indexed citations. Recurring topics across this work include Machine Learning and Algorithms (21 papers), Neural Networks and Applications (16 papers), Machine Learning and Data Classification (14 papers), Face and Expression Recognition (10 papers), Gaussian Processes and Bayesian Inference (9 papers), Advanced Bandit Algorithms Research (8 papers), Algorithms and Data Compression (5 papers) and Recommender Systems and Techniques (4 papers). The work is most often cited by research in Artificial Intelligence (2.1k citations), Computer Vision and Pattern Recognition (997 citations), Information Systems (794 citations), Signal Processing (358 citations) and Management Science and Operations Research (412 citations). Ralf Herbrich has collaborated with scholars based in United Kingdom, United States and Germany. Frequent co-authors include Thore Graepel, Joaquin Quiñonero Candela, Neil D. Lawrence, David Stern, Matthias Seeger, Arthur Gretton, Bernhard Schölkopf, Ou Jin, Bo Liu and Tian-Bing Xu. Their work appears in journals such as Journal of Machine Learning Research, IEEE Transactions on Information Theory, Machine Learning, The MIT Press eBooks and Infoscience (Ecole Polytechnique Fédérale de Lausanne).
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.