Unlike a course on traditional statistics, statistical machine learning is particularly focused on the analysis of data in high dimension, as well as the efficiency of algorithms to process the large amount of data encountered in multiple application areas such as image or sound analysis, natural language processing, bioinformatics or finance.

The objective of this class is to present the main theories and algorithms in statistical machine learning. The methods covered will rely amongst others on convex analysis arguments. The practical sessions (more than half of which will be realized with computers) will lead to simple implementations of the algorithms seen in class and with applications to various domains such as computer vision or natural language processing.

Teachers: Pierre Gaillard and Alessandro Rudi.

Practical sessions: Raphaël Berthier.

The class will last 52 hours (30 hours of class + 22 hours of practical sessions) and can be validated for 9 ECTS.

Final grade: 50% final exam, 50% homework.

Previous years: Fall 2018, 2017, 2016, 2015, 2014, 2013, 2012

# | Date | Teacher | Title |
---|---|---|---|

1 | 05/02/2019 | A. Rudi
P. Gaillard |
Introduction
TD0 (Python test file) |

2 | 12/02/2019 | P. Gaillard
R. Berthier |
Linear regression
TD1 (Data: classificationA_train, classificationA_test, classificationB_train, classificationB_test, classificationC_train, classificationC_test, mnist_digits.mat), solution |

3 | 19/02/2019 | A. Rudi
R. Berthier |
Statistical properties in ML
(PW) |

4 | 26/02/2019 | A. Rudi
R. Berthier |
KNN
(PW) |

5 | 12/03/2019 | P. Gaillard
R. Berthier |
Logistic regression and convex analysis
(PW) |

6 | 19/03/2019 | P. Gaillard
R. Berthier |
Convex optimization
(PW) -- first assignment available |

7 | 02/04/2019 | P. Gaillard
R. Berthier |
Online learning
(PW) |

8 | 09/04/2019 | P. Gaillard
R. Berthier |
High dimensional statistics
(PW) -- first assignment due date |

9 | 16/04/2019 | P. Gaillard
R. Berthier |
Model based machine learning: maximum likelihood
(PW) |

10 | 30/04/2019 | A. Rudi
R. Berthier |
Kernels
(PW) |

11 | 07/05/2019 | A. Rudi
R. Berthier |
Neural networks
(PW) -- second assignment available |

12 | 14/05/2019 | P. Gaillard
R. Berthier |
Non-supervised learning
(PW) |

13 | 21/05/2019 | A. Rudi
R. Berthier |
Summary
Exercises -- second assignment due date |

14 | 28/05/2019 | P. Gaillard | Exam |