David CHATEL
Author's posts
Sep 22
Projet de Master : Propagation d’étiquettes structurées pour le traitement automatique des langues
Titre : Propagation d’étiquettes structurées pour le traitement automatique des langues Equipe : MAGNET Responsable HDR : Marc Tommasi Encadrant : Pascal Denis Problématique : Le traitement automatique des langues (TAL) offre deux défis centraux aux algorithmes d’apprentissage automatique: d’une part, la très grande dimensionalité de leur espace des sorties (leur nombre est le plus …
Jul 03
A Markov random field approach to online graph label prediction
when: July 2, 2014 where: salle plénière speaker: Mark Herbster title: A Markov random field approach to online graph label prediction abstract: In graph label prediction each vertex is labeled with a 0 or 1. The aim is given a partial labeling of the graph to extend to a complete labeling. A common approach to …
Jul 03
Online Bayesian Moment Matching for Latent Dirichlet Allocation
when: may 20, 2014 from 11 am to noon where: A00 speaker: Pascal Poupart title: Online Bayesian Moment Matching for Latent Dirichlet Allocation abstract: Latent Dirichlet Allocation (LDA) is one of the most important models for the unsupervised discovery of latent components such as topics, entities and relations based on unlabeled corpora. The estimation of …
Jul 03
Spectral Bandits for Smooth Graph Functions
when: may 16, 2014 from 11 am where: A00 Speaker: Tomáš Kocák title: Spectral Bandits for Smooth Graph Functions abstract: Smooth functions on graphs have wide applications in manifold and semi-supervised learning. In this paper, we study a bandit problem where the payoffs of arms are smooth on a graph. This framework is suitable for …
Jul 03
MLSS Summer school
when: april 25, 2014 to may 4, 2014 where: iceland The Machine Learning Summer School will take place at Reykjavik University in Reykjavik, Iceland, from April 25 to May 4, 2014. The field of machine learning is at the intersection of computer science, statistics, mathematics, and optimization. The Machine Learning Summer School (MLSS) is a …
Jul 03
The total variation on hypergraphs – Learning on hypergraphs revisited
when: April 4, 2014 from 11 am to noon where: room B21 speaker: Shyam Sundar title: The total variation on hypergraphs – Learning on hypergraphs revisited abstract: In this talk, I present a new learning framework on hypergraphs which, unlike the existing methods, fully uses the hypergraph structure. The key element in our learning framework (for …
Jul 03
Network‐based Prediction of Adverse Drug Events and Interactions
when: Thursday, March 20th, 2014 3:00PM-4:00PM where: room B21 (bât. B, ave Halley) speaker: Aurel Cami title: Network‐based Prediction of Adverse Drug Events and Interactions abstract: Adverse drug events (ADEs) and drug‐drug interactions (DDIs) are a serious concern for Public Health and the pharmaceutical industry. Every year, millions of patients are affected by drug adverse …
Jul 03
Diffusion strategies for cooperative reinforcement learning
When: February 14, 2014 from 11 AM to noon Where: room W01 Speaker: Sergio Valcarcel Title: Diffusion strategies for cooperative reinforcement learning Abstract: We will introduce diffusion strategies and apply them to develop fully-distributed cooperative reinforcement learning solutions, in which agents in a network communicate only with their immediate neighbors to improve predictions about their …
Jul 03
Online Clustering of Bandits (in a Social Network)
When: January 17, 2014 from 11AM to noon Where: room B21 Speaker: Claudio Gentile Title: Online Clustering of Bandits (in a Social Network) Abstract: Bandit algorithms have become a standard tool for facing the the so-called exploration-exploitation dilemma that naturally arises in learning problems with partial information. Recommendation systems are one of the best applications …
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