Master
2021/2022
High-dimensional Statistical Methods
Type:
Compulsory course
Area of studies:
Applied Mathematics and Informatics
Delivered by:
School of Data Analysis and Artificial Intelligence
Where:
Faculty of Computer Science
When:
1 year, 3 module
Mode of studies:
offline
Open to:
students of one campus
Instructors:
Quentin Paris
Master’s programme:
Math of Machine Learning
Language:
English
ECTS credits:
6
Contact hours:
32
Course Syllabus
Abstract
The course presents an introduction to modern statistical and probabilistic methods for data analysis, emphasising finite sample guarantees and problems arising from high-dimensional data. The course is mathematically oriented and level of the material ranges from a solid undergraduate to a graduate level. Topics studied include for instance Concentration Inequalities, High Dimensional Linear Regression and Matrix estimation. Prerequisite: Probability Theory.