Aymeric Dieuleveut
- Artificial Intelligence
- Computational Mechanics
- Statistics and Probability
- Computational Theory and Mathematics
- Numerical Analysis
- Co-authors
- Francis BachAlain DurmusÉric MoulinesAdrien TaylorGersende FortKumar Kshitij PatelHoi-To WaiJulien M. Hendrickx
- Topics
- Stochastic Gradient Optimization Techniques (9 papers)Sparse and Compressive Sensing Techniques (7 papers)Advanced Optimization Algorithms Research (3 papers)
In The Last Decade
Aymeric Dieuleveut
11 papers receiving 54 citations
Peers
Comparison fields: 5 of 23
- Artificial Intelligence 38
- Computational Mechanics 17
- Statistics and Probability 17
- Computational Theory and Mathematics 9
- Numerical Analysis 8
Countries citing papers authored by Aymeric Dieuleveut
This map shows the geographic impact of Aymeric Dieuleveut'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 Aymeric Dieuleveut with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Aymeric Dieuleveut more than expected).
Fields of papers citing papers by Aymeric Dieuleveut
This network shows the impact of papers produced by Aymeric Dieuleveut. 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 Aymeric Dieuleveut. The network helps show where Aymeric Dieuleveut may publish in the future.
Co-authorship network of co-authors of Aymeric Dieuleveut
This figure shows the co-authorship network connecting the top 25 collaborators of Aymeric Dieuleveut. A scholar is included among the top collaborators of Aymeric Dieuleveut based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Aymeric Dieuleveut. Aymeric Dieuleveut is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 9 | |
| 3 | 2 | |
| 4 | 3 | |
| 5 | 2 | |
| 6 | Federated-EM with heterogeneity mitigation and variance reduction | 3 |
| 7 | Debiasing Averaged Stochastic Gradient Descent to handle missing values | 1 |
| 8 | 26 | |
| 9 | 1 | |
| 10 | Communication trade-offs for Local-SGD with large step size | 4 |
| 11 | Wasserstein is all you need. | 1 |
| 12 | 2 |
About Aymeric Dieuleveut
Aymeric Dieuleveut is a scholar working on Numerical Analysis, Statistics and Probability and Artificial Intelligence, having authored 12 papers that have together received 56 indexed citations. Recurring topics across this work include Stochastic Gradient Optimization Techniques (9 papers), Sparse and Compressive Sensing Techniques (7 papers) and Advanced Optimization Algorithms Research (3 papers). The work is most often cited by research in Statistics and Probability (17 citations), Numerical Analysis (8 citations) and Artificial Intelligence (38 citations). Aymeric Dieuleveut has collaborated with scholars based in France, Burundi and Belgium. Frequent co-authors include Francis Bach, Alain Durmus, Éric Moulines, Adrien Taylor, Gersende Fort, Kumar Kshitij Patel, Hoi-To Wai, Julien M. Hendrickx, Andreas Hug and François Glineur. Their work appears in journals such as IEEE Transactions on Signal Processing, The Annals of Statistics and Mathematical Programming Computation.
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.