Secretariat for Master of Mathematics
- Mzia Goguadze
- office D200
- 01 49 40 28 10
Formation | M2 EID2 M2 Mathematics for Data |
Semester | 1 |
Bloc | Data sciences and machine learning |
Teaching staff | Lectures : Basarab Matei. TA Sessions : |
Credits | 3 ECTS |
Teaching hours | 15h of lecture + 15h of TA session |
Validation scheme | Continuous examination+final exam |
Setting of the Learning Problem - Consistency of Learning Processes - Bounds on the Rate of Convergence of Learning Processes - Controlling the Generalization Ability of Learning Processes - Methods of Pattern Recognition - Methods of Function Estimation - Direct Methods in Statistical Learning Theory - The Vicinal Risk Minimization Principle and the Kernel Methods - Hidden Markov Models - Maximum likelihood for the HMM - The forward-backward algorithm - The Viterbi algorithm - Linear Dynamical Systems.