Cтуденческие и аспирантские проекты

В настоящем разделе представлены некоторые текущие научные проекты лаборатории. Если вы студент бакалавриата, магистратуры или аспирант и хотите решать задачи под руководством сотрудников лаборатории, то вы можете выбрать одну из понравившихся тем и связаться с соответствующим сотрудником лаборатории.
 

Old talks and posters of (BS, MS, PhD) students:

• L. Iosipoi:
  1. MCMC for heavy-tailed distributions with known characteristic function and unknown density (poster, Structural inference in high-dimensional models - 2, 2019); 
  2. Comparing LS and EVM in Variance Reduction (poster, Structural Inference in high-dimensional models, 2018);
  3. Variance reduction in Monte-Carlo via Empirical Variance Minimization (talk, winter school New frontiers in high-dimensional probability and statistics, 2018); 
• M. Kaledin:
  1. Approximate Dynamic Programming for American Options (poster, Structural inference in high-dimensional models - 2, 2019); 
• A. Kroshin:
  1. CLT and confidence sets in 2-Wasserstein space (poster, Structural Inference in high-dimensional models, 2018);
  2. Law of Large Numbers and Central Limit Theorem for Wasserstein Barycenters (talk, winter school New frontiers in high-dimensional probability and statistics, 2018);
• N. Puchkin:

  1. Structure-adaptive manifold estimation (poster, Structural inference in high-dimensional models - 2, 2019); 

  2. Pointwise adaptation via stagewise aggregation of local estimates for multiclass classification (poster 2018 IMS Annual Meeting on Probability and Statistics, 2018);
  3. Pointwise adaptation via stagewise aggregation of local estimates for multiclass classification (talk at winter school New frontiers in high-dimensional probability and statistics, 2018); 
• S. Samsonov:
  1. Variance Reduction for Dependent Sequences via Empirical Variance Minimisation (poster, Structural Inference in high-dimensional models 2, 2019);
• V. Shumovskaia:
  1. Towards Hypothesis Testing for Random Graphs with Community Structure (poster, Structural Inference in high-dimensional models, 2018);
• I. Silin: On the posterior distribution of covariance matrix (talk, winter school New frontiers in high-dimensional probability and statistics, 2018);
• Y. Tavyrikov: Approximate Dynamic Programming (talk, winter school New frontiers in high-dimensional probability and statistics, 2018);