Classes will take place on Wednesdays from 9am to 12pm at ENS Cachan, in Amphi Curie.
Moodle for the class.
Below is the tentative schedule, with scribe notes from last year that might be updated for some lectures.
|Date||Lecturer||Topics||Corresponding chapters in class notes||Scribe notes|
|Huu Dien Khue Le, Robin Benesse
Generative classification (Fisher discriminant)
|Aymeric Reshef, Claire Vernade
Marie d’Autume, Jean-Baptiste Alayrac
||Simon Lacoste-Julien||Graph theory
Directed graphical models
Undirected graphical models
||Jaime Roquero, JieYing Wu
||Simon Lacoste-Julien||Exponential families
|Thomas Belhalfaoui, Lénaïc Chizat
||Francis Bach||Gaussian variables
||Lucas Plaetevoet, Ismael Belghiti
||Simon Lacoste-Julien||Sum-product algorithm
|Pauline Luc, Mathieu Andreux
||Guillaume Obozinski||Approximate inference I
||Khalife Sammy, Maryan Morel
||Guillaume Obozinski||Approximate inference II
||Basile Clément, Nathan de Lara
||Simon Lacoste-Julien||Bayesian methods
| 5.1 and 5.3
|Gauthier Gidel, Lilian Besson
Batiment Cournot (C102-103)
|Project poster session|
Homework 1, due October 24th, 2015 (on the Moodle): Homework | Data.
Homework 2, due November 11th, 2015 (on the Moodle): Homework | Data
Homework 3, due January 6th, 2016 (on the Moodle; we highly recommend you submit it in December though): Homework | Data
The final project allows a further understanding of certain aspects of the course. The following schedule has to be respected.
|November||Choose a project (one or two students per projects, preferably two)|
|Before 11/18||Send an email to the three teachers, in which all members of your team are cc'ed to request our agreement on your choice of team and project topic.|
|Before 12/09||Send a draft (1 page) + first results, on the Moodle.|
|On 2016/01/06||Poster session in Batiment Cournot (C102-103) - 9am to 12pm|
|Before 2016/01/13||Submit your project report (~6 pages, on the Moodle)|
This course provides a unifying introduction to probabilistic modelling through the framework of graphical models, together with their associated learning and inference algorithms.
The course will be based on the book in preparation of Michael Jordan (UC Berkeley). Printed version of parts of the book (playing the role of the "polycopie") will be available from the Master's administrative assistant one or two weeks after the beginning of classes. We will notify you when they are ready for you to go and pick them up.
Last updated: December 2nd, 2015.