Master2 Data Sciences

Theoretical guidelines for high-dimensional data analysis

These lectures are offered in the M2 Data Sciences


28/11: room 0A1, Institut de Mathématiqued d'Orsay, 14h-18h
05/12: room 0A1, Institut de Mathématiqued d'Orsay, 14h-18h
12/12: amphi Yoccoz, Institut de Mathématiqued d'Orsay, 14h-18h
19/12: room 0A1, Institut de Mathématiqued d'Orsay, 14h-18h
09/01: room 0A1, Institut de Mathématiqued d'Orsay, 14h-18h


The Institut de Mathématiques d'Orsay is located in Building 307, Orsay campus, 5min walk from RER station Orsay-Ville.
Access plan


This course is intended as a theoretical reflexion on the practice of data analysis. It is not suited as a training for a PhD in mathematical statistics. You should instead follow the course Statistiques en grande dimension offered in the Master2 StatML and PS and MSV.


Goal of the lectures: The lecture will be based on some recent research papers (How to read a paper?). The list of the research papers below is subject to change before the start of the lectures. The presence during the lectures is mandatory and taken into account in the final evaluation.

Paper(s)SlidesFurther reading
1Strength and weakness of the Lasso
Slides No free computationnal lunch
2False discoveries, multiple testing, online issue and link to bandits problems
Paper Slides
Reliability of scientific findings? Quality Preserving Databases? Online FDR control
3Adaptive data analysis
Slides Kaggle overfiting
4Curse of dimensionality. When interpolation meets underfitting
Slides and Lecture notes Robust PCA
5Robust learning
Paper Slides Learning with Median Of Means


The reports must be sent by email by February 15 in a zip file including:
- the report in pdf format (10 to 20 pages)
- the source code for the numerics
Look at the instructions for your report!