2023/2024
***Instructors:| Date | Time | Room number | Instructor | Session | Topics | Material |
| Tuesday October 3 |
08:30-10:30 | 1Z34 | N. Vayatis | Lecture #1 | Chapter 1 - Optimality in binary
classification Data/Objectives/Optimal elements/ERM |
Slides LDA |
| Tuesday October 10 |
08:30-10:30 | 1Z34 | N. Vayatis | Lecture #2 | Chapter 1 - Optimality in statistical learning Other problems/Complexity of learning |
Slides |
| Tuesday October 17 |
08:30-10:30 | 1Z34 | G. Serré | Exercise session #1 | Optimal elements |
Set |
| Tuesday October 24 |
08:30-10:30 | 1Z34 | N. Vayatis | Lecture #3 | Chapter 2 - Mathematical foundations (I) Probabilistic inequalities, complexity measures |
Slides |
| Tuesday October 31 |
08:30-10:30 | 1Z34 | M. Garin | Exercise session #2 | Inequalities, Rademacher complexity, VC
dimension |
Set |
| Tuesday November 7 |
08:30-10:30 | 1Z34 | Partial exam - Mandatory No documents |
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| Tuesday November 14 |
08:30-10:30 | 1Z34 | N. Vayatis | Lecture #4 | Chapter 2 - Mathematical foundations (II) Regularization and stability |
Slides Link |
| Tuesday November 21 |
08:30-10:30 | 1Z34 | N. Vayatis | Lecture #5 | Chapter 3 - Consistency of Machine Learning methods (I) Margin bounds and application to SVM |
Slides |
| Tuesday November 28 | 08:30-10:30 | 1Z34 | G. Serré | Exercise session #3 | Consistency and convergence bounds |
Set |
| Tuesday December 5 |
08:30-10:30 | 1Z34 | N. Vayatis | Lecture #6 | Chapter 3 - Consistency of Machine Learning methods (II) Ensemble methods: Bagging, Random Forests, Boosting |
Slides |
| Tuesday December 12 | 08:30-10:30 | 1Z34 | N. Vayatis | Lecture #7 | Chapter
3 - Consistency of Machine Learning methods (III) Neural networks, Mirror Descent |
Slides |
| Tuesday December 19 | 08:30-10:30 | 1Z34 | M. Garin | Exercise session #4 | Course wrap-up |
Set |
| Monday January 8 |
08:30-10:30 | 1Z34 | Final exam - Mandatory Documents allowed |