Dmitry Kropotov
- Senior Lecturer:Faculty of Computer Science / Big Data and Information Retrieval School
- Senior Research Fellow:Faculty of Computer Science / Big Data and Information Retrieval School / Samsung-HSE Laboratory
- Dmitry Kropotov has been at HSE since 2017.
Courses (2018/2019)
- Continuous Optimization (Bachelor’s programme; Faculty of Computer Science; programme "Applied Mathematics and Information Science"; 3 year, 3 module)Rus
- Past Courses
Courses (2017/2018)
Continuous Optimization (Bachelor’s programme; Faculty of Computer Science; programme "Applied Mathematics and Information Science"; 3 year, 3 module)Rus
Publications3
- Chapter Izmailov P., Novikov A., Kropotov D. Scalable Gaussian Processes with Billions of Inducing Inputs via Tensor Train Decomposition, in: Proceedings of Machine Learning Research. Proceedings of The International Conference on Artificial Intelligence and Statistics (AISTATS 2018). , 2018. P. 726-735.
- Article Izmailov P., Kropotov D. Faster variational inducing input Gaussian process classification // Journal of machine learning and data analysis. 2017. Vol. 3. No. 1. P. 20-35. doi
- Chapter Rodomanov A., Kropotov D. A Superlinearly-Convergent Proximal Newton-type Method for the Optimization of Finite Sums, in: Proceedings of Machine Learning Research. Proceedings of the International Conference on Machine Learning (ICML 2016) Vol. 48. NY : , 2016. P. 2597-2605.
Conferences
- 2018
The 21st International Conference on Artificial Intelligence and Statistics (AISTATS 2018) (Плайя-Бланка, Ланзароте, Канарские острова). Presentation: Scalable Gaussian Processes with Billions of Inducing Inputs via Tensor Train Decomposition
- 2016
The 33rd International Conference on Machine Learning (ICML 2016) (Нью-Йорк). Presentation: A Superlinearly-Convergent Proximal Newton-Type Method for the Optimization of Finite Sums
