Fullscreen
Loading...
 
Tao
Print

Seminar28062018

June, Thursday 28th

14:30 (Shannon amphitheatre, 660 building) (see location )

Alexandre Aussem

(LIRIS - Lyon)

Title: Identifying irreducible disjoint factors in multivariate probability distributions: Application to multilabel learning


Abstract

In this talk, I discuss the problem of decomposing a multivariate probability distribution into a product of factors defined over disjoint subsets of random variables called irreducible disjoint factors (IDFs). I show that the IDFs are the connected components of an undirected graphical model which structure can be inferred by running a series of conditional independence tests. Several theoretical results are established to characterize the IDFs under various assumptions about the probability distribution (i.e., DAG-Faithfulness, Intersection property, Composition property). I show how the IDF decomposition can help to identify the bayes optimal solution of the multi-label classification problem using the subset zero-one loss or the F-measure.



Contact: guillaume.charpiat at inria.fr
All TAU seminars: here


Contributors to this page: guillaume .
Page last modified on Tuesday 26 of June, 2018 16:59:09 CEST by guillaume.