Alexey Kroshnin
- Senior Research Fellow:Faculty of Computer Science / AI and Digital Science Institute / International Laboratory of Stochastic Algorithms and High-Dimensional Inference
- Alexey Kroshnin has been at HSE University since 2018.
Education and Degrees
- 2022
PhD
University of Lyon - 2018
Master's
Moscow Institute of Physics and Technology - 2016
Bachelor's in Applied Mathematics and Applied Physics
Moscow Institute of Physics and Technology
Publications8
- Article Kubentayeva M., Yarmoshik D., Persiianov M., Kroshnin Alexey, Kotliarova E., Tupitsa N., Pasechnyuk D., Gasnikov Alexander, Shvetsov V., Baryshev L., Shurupov A. Primal-dual gradient methods for searching network equilibria in combined models with nested choice structure and capacity constraints // Computational Management Science. 2024. Vol. 21. Article 15. doi
- Article Kroshnin A., Eugene Stepanov, Trevisan D. Infinite multidimensional scaling for metric measure spaces // ESAIM - Control, Optimisation and Calculus of Variations. 2022. Vol. 28. Article 58. doi
- Article Carlier G., Eichinger K., Kroshnin A. Entropic-Wasserstein Barycenters: PDE Characterization, Regularity, and CLT // SIAM Journal on Mathematical Analysis. 2021. Vol. 53. No. 5. P. 5880-5914. doi
- Article Klochkov Y., Kroshnin A., Zhivotovskiy N. Robust k-means clustering for distributions with two moments // Annals of Statistics. 2021. Vol. 49. No. 4. P. 2206-2230. doi
- Article Kroshnin A., Spokoiny V., Suvorikova A. Statistical inference for Bures-Wasserstein barycenters // Annals of Applied Probability. 2021. Vol. 31. No. 3. P. 1264-1298. doi
- Chapter Kroshnin A., Tupitsa Nazarii, Dvinskikh D., Dvurechensky P., Gasnikov Alexander, Uribe C. A. On the Complexity of Approximating Wasserstein Barycenters, in: Proceedings of Machine Learning Research Vol. 97: International Conference on Machine Learning, 9-15 June 2019, Long Beach, California, USA. PMLR, 2019. P. 3530-3540.
- Chapter Dvurechensky P., Gasnikov A., Kroshnin A. Computational optimal transport: Complexity by accelerated gradient descent is better than by Sinkhorn's algorithm, in: Proceedings of the 35th International Conference on Machine Learning (2018) Vol. 80. PMLR, 2018. P. 1367-1376.
- Article Kroshnin A. Fréchet Barycenters in the Monge-Kantorovich Spaces // Journal of Convex Analysis. 2018. Vol. 25. No. 4. P. 1371-1395.