Modeling Moscow Institute of Physics and Technology
Лекция Applied statistics in machine learning
Должность: Ведущий научный сотрудник
Main methods of applied statistics and machine learning are considered, namely, probability density estimation, bootstrap, hypothesis testing, linear regression analysis, sensitivity analysis, dimension reduction, efficient dimension reduction, regression based on parametric dictionaries, bayesian regression based on gaussian processes, bayesian optimization based on gaussian processes, etc. Applications are illustrated on basis of industrial problems of surrogate modeling and optimization.
Structural diagnostics in technical, economical, and natural processes
Modeling and optimization of complex systems
Structural adaptive inference
Stochastic optimization and optimal stopping