Tim van Erven
- Statistics and Probability top 5%
- Artificial Intelligence top 5%
- Machine Learning and Algorithms 8
- Data Stream Mining Techniques 3
- Bayesian Methods and Mixture Models 2
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- Advanced Bandit Algorithms Research 11
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- Sparse and Compressive Sensing Techniques 2
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- Distributed Sensor Networks and Detection Algorithms 2
- Optimization and Search Problems 2
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- Wireless Communication Security Techniques 2
- Co-authors
- Peter HarremoësPeter GrünwaldSteven de RooijWouter M. KoolenRobert C. WilliamsonManfred K. WarmuthNishant A. MehtaMark D. Reid
- Journals
- Journal of Machine Learning Research (1 paper)IEEE Transactions on Information Theory (1 paper)Journal of the Royal Statistical Society Series B (Statistical Methodology) (1 paper)
- Partner nations
- NetherlandsAustraliaUnited Kingdom
In The Last Decade
Tim van Erven
16 papers receiving 909 citations
Hit Papers
Peers
Comparison fields: 5 of 117
- Statistics and Probability 125
- Artificial Intelligence 460
- Statistical and Nonlinear Physics 147
- Management Science and Operations Research 111
- Computational Mathematics 4
Countries citing papers authored by Tim van Erven
This map shows the geographic impact of Tim van Erven'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 Tim van Erven with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tim van Erven more than expected).
Fields of papers citing papers by Tim van Erven
This network shows the impact of papers produced by Tim van Erven. 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 Tim van Erven. The network helps show where Tim van Erven may publish in the future.
Co-authorship network
The 9 scholars most cited alongside Tim van Erven, 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 | Robust Online Convex Optimization in the Presence of Outliers | 2021 | 2 |
| 2 | Open problem: Fast and optimal online portfolio selection | 2020 | 1 |
| 3 | The Many Faces of Exponential Weights in Online Learning | 2018 | 1 |
| 4 | 2016 | 5 | |
| 5 | 2015 | 18 | |
| 6 | Second-order quantile methods for experts and combinatorial games | 2015 | 4 |
| 7 | Learning the Learning Rate for Prediction with Expert Advice | 2014 | 3 |
| 8 | Follow the Leader with Dropout Perturbations | 2014 | 14 |
| 9 | Rényi Divergence and Kullback-Leibler Divergencebreakdown → | 2014 | 802 |
| 10 | From Exp-concavity to Mixability | 2013 | 2 |
| 11 | 2012 | 37 | |
| 12 | Adaptive Hedge | 2011 | 8 |
| 13 | MIXABILITY IS BAYES RISK CURVATURE RELATIVE TO LOG LOSS | 2011 | 6 |
| 14 | 2010 | 27 | |
| 15 | Rényi Divergence and Its Properties | 2010 | 1 |
| 16 | Learning the Switching Rate by Discretising Bernoulli Sources Online | 2009 | 8 |
| 17 | Catching Up Faster in Bayesian Model Selection and Model Averaging | 2007 | 8 |
About Tim van Erven
Tim van Erven is a scholar working on Management Science and Operations Research, Statistics and Probability, Artificial Intelligence, Applied Mathematics and Numerical Analysis, having authored 17 papers that have together received 947 indexed citations. Recurring topics across this work include Advanced Bandit Algorithms Research (11 papers), Machine Learning and Algorithms (8 papers), Data Stream Mining Techniques (3 papers), Sparse and Compressive Sensing Techniques (2 papers), Distributed Sensor Networks and Detection Algorithms (2 papers), Bayesian Methods and Mixture Models (2 papers), Optimization and Search Problems (2 papers) and Wireless Communication Security Techniques (2 papers). The work is most often cited by research in Statistics and Probability (125 citations), Artificial Intelligence (460 citations), Statistical and Nonlinear Physics (147 citations), Management Science and Operations Research (111 citations) and Computational Mathematics (4 citations). Tim van Erven has collaborated with scholars based in Netherlands, Australia and United Kingdom. Frequent co-authors include Peter Harremoës, Peter Grünwald, Steven de Rooij, Wouter M. Koolen, Robert C. Williamson, Manfred K. Warmuth, Nishant A. Mehta, Mark D. Reid and Wojciech Kotłowski. Their work appears in journals such as Journal of Machine Learning Research, IEEE Transactions on Information Theory, Journal of the Royal Statistical Society Series B (Statistical Methodology), ANU Open Research (Australian National University) and Conference on Learning Theory.
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.