Peter Richtárik
Impact in
- Numerical Analysis top 2%
- Advanced Optimization Algorithms Research
- Computational Mechanics top 1%
- Sparse and Compressive Sensing Techniques
Papers in
-
- Stochastic Gradient Optimization Techniques 55
- Privacy-Preserving Technologies in Data 11
- Machine Learning and Algorithms 4
-
- Sparse and Compressive Sensing Techniques 44
- Co-authors
- Martin Takáč (10 shared papers)Jakub Konečný (6 shared papers)Olivier Fercoq (2 shared papers)Zheng Qu (8 shared papers)Jie Liu (1 shared paper)Antonin Chambolle (2 shared papers)Matthias J. Ehrhardt (2 shared papers)Michael I. Jordan (2 shared papers)
- Journals
- Optimization methods & software (6 papers)Journal of Optimization Theory and Applications (4 papers)SIAM Journal on Optimization (4 papers)Mathematical Programming (2 papers)Linear Algebra and its Applications (2 papers)
- Partner nations
- Saudi ArabiaUnited KingdomUnited States
In The Last Decade
Peter Richtárik
66 papers receiving 1.6k citations
Peter Richtárik's Hit Papers
Peers
Comparison fields: 5 of 100
- Numerical Analysis 282
- Computational Mechanics 828
- Artificial Intelligence 1.1k
- Computational Mathematics 19
- Statistics and Probability 166
Countries citing papers authored by Peter Richtárik
This map shows the geographic impact of Peter Richtárik'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 Peter Richtárik with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peter Richtárik more than expected).
Fields of papers citing papers by Peter Richtárik
This network shows the impact of papers produced by Peter Richtárik. 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 Peter Richtárik. The network helps show where Peter Richtárik may publish in the future.
Co-authors
The 25 scholars most cited alongside Peter Richtárik, 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 70 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Iteration complexity of randomized block-coordinate descent methods for minimizing a composite function Hit paper breakdown → | 2012 | 347 |
| 2 | 2015 | 192 | |
| 3 | 2015 | 151 | |
| 4 | 2017 | 125 | |
| 5 | 2015 | 111 | |
| 6 | 2013 | 79 | |
| 7 | 2018 | 76 | |
| 8 | 2017 | 56 | |
| 9 | 2018 | 35 | |
| 10 | Mini-Batch Primal and Dual Methods for SVMs | 2013 | 31 |
| 11 | 2022 | 29 | |
| 12 | 2018 | 28 | |
| 13 | 2015 | 27 | |
| 14 | 2017 | 25 | |
| 15 | From Local SGD to Local Fixed Point Methods for Federated Learning | 2020 | 24 |
| 16 | 2019 | 23 | |
| 17 | 2021 | 22 | |
| 18 | 2016 | 21 | |
| 19 | Even faster accelerated coordinate descent using non-uniform sampling | 2016 | 20 |
| 20 | 2016 | 20 |
About Peter Richtárik
Peter Richtárik is a scholar working on Artificial Intelligence, Computational Mechanics, Computational Theory and Mathematics, Statistics and Probability and Numerical Analysis, having authored 70 papers that have together received 1.7k indexed citations. Recurring topics across this work include Stochastic Gradient Optimization Techniques (55 papers), Sparse and Compressive Sensing Techniques (44 papers), Privacy-Preserving Technologies in Data (11 papers), Markov Chains and Monte Carlo Methods (10 papers), Advanced Optimization Algorithms Research (9 papers), Statistical Methods and Inference (7 papers), Complexity and Algorithms in Graphs (7 papers) and Machine Learning and Algorithms (4 papers). The work is most often cited by research in Numerical Analysis (282 citations), Computational Mechanics (828 citations), Artificial Intelligence (1.1k citations), Computational Mathematics (19 citations) and Statistics and Probability (166 citations). Peter Richtárik has collaborated with scholars based in Saudi Arabia, United Kingdom and United States. Frequent co-authors include Martin Takáč, Jakub Konečný, Olivier Fercoq, Zheng Qu, Jie Liu, Antonin Chambolle, Matthias J. Ehrhardt, Michael I. Jordan, Carola‐Bibiane Schönlieb and Chenxin Ma. Their work appears in journals such as Optimization methods & software, Journal of Optimization Theory and Applications, SIAM Journal on Optimization, Mathematical Programming and Linear Algebra and its Applications.
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.