MAGNET - 2018 - Annual activity report

MAGNET

MAGNET - 2018

Project-Team Magnet

Team, Visitors, External Collaborators

Overall Objectives

Presentation

Research Program

Application Domains

Domain 1

Highlights of the Year

New Software and Platforms

New Results

On the Bernstein-Hoeffding Method
IncGraph: Incremental graphlet counting for topology optimisation
Graph sampling with applications to estimating the number of pattern embeddings and the parameters of a statistical relational model
A machine learning based framework to identify and classify long terminal repeat retrotransposons
A Distributed Frank-Wolfe Framework for Learning Low-Rank Matrices with the Trace Norm
Personalized and Private Peer-to-Peer Machine Learning
Hiding in the Crowd: A Massively Distributed Algorithm for Private Averaging with Malicious Adversaries
A Probabilistic Model for Joint Learning of Word Embeddings from Texts and Images
A Framework for Understanding the Role of Morphology in Universal Dependency Parsing
Online Reciprocal Recommendation with Theoretical Performance Guarantees
On Similarity Prediction and Pairwise Clustering
A Probabilistic Theory of Supervised Similarity Learning for Pointwise ROC Curve Optimization
Escaping the Curse of Dimensionality in Similarity Learning: Efficient Frank-Wolfe Algorithm and Generalization Bounds
Nonstochastic Bandits with Composite Anonymous Feedback

Bilateral Contracts and Grants with Industry

Partnerships and Cooperations

Dissemination

Bibliography

Previous |

Home | Next next

Section: Dissemination

Teaching - Supervision - Juries

Teaching

Licence SHS: Joël Legrand , Traitement de textes et tableur, 10h, L1, Université Lille.
Licence SHS: Marc Tommasi , Langages du Web, 24h, L2, Université Lille.
Licence MIASHS: Mikaela Keller , Python 1, 40h, L1, Université Lille.
Licence MIASHS: Marc Tommasi , Codage et représentation de l'information, 48h, L1, Université Lille.
Licence MIASHS: Mikaela Keller , Codage et représentation de l'information, 42h, L1, Université Lille.
Licence SoQ (SHS): Mikaela Keller , Algorithmique de graphes, 24h, L3, Université Lille.
Licence Marc Tommasi C2i 12h, Université Lille.
Licence Marc Tommasi Humanités numériques - Découvrir et faire découvrir la programmation, 20h, Université Lille/
Master MIASHS: Mikaela Keller , Algorithmes fondamentaux de la fouille de données, 60h, M1, Université Lille.
Master MIASHS: Joël Legrand , Apprentissage et émergence de comportements, 30h, M2, Université Lille.
Master Data Analysis & Decision Making: Aurélien Bellet , Machine Learning, 12h, Ecole Centrale de Lille.
Master / Master Spécialisé Big Data: Aurélien Bellet , Advanced Machine Learning, 15h, Télécom ParisTech.
Formation continue (Certificat d’Études Spécialisées Data Scientist): Aurélien Bellet , Supervised Learning and Support Vector Machines, 17.5h, Télécom ParisTech.
Master Informatique: Pascal Denis , Fondements de l'Apprentissage Automatique, 46h, M1, Université de Lille.

Supervision

Postdoc: Melissa Ailem , InriaSiliconValley postdoctoral grant, supervised by Aurélien Bellet , Marc Tommasi , Pascal Denis and Fei Sha (University of Southern California).
Postdoc: Bo Li , supervised by Pascal Denis on ANR REM, Model Sense Disambiguation, since December 2017.
PhD: Géraud Le Falher , Characterizing edges in signed and vector-valued graphs. April 16th 2018, Marc Tommasi and Fabio Vitale and Claudio Gentile .
Phd: Ashraf M. Kibriya , Mining Frequent Patterns in Large Networks, June 2018, Jan Ramon .
PhD in progress: Mathieu Dehouck , Graph-based Learning for Multi-lingual and Multi-domain Dependency Parsing, since Oct 2015, Pascal Denis and Marc Tommasi .
PhD in progress: Onkar Pandit , Graph-based Semi-supervised Linguistic Structure Prediction, since Dec. 2017, Pascal Denis , Marc Tommasi and Liva Ralaivola (University of Marseille).
PhD in progress: Mariana Vargas Vieyra , Adaptive Graph Learning with Applications to Natural Language Processing, since Jan. 2018. Pascal Denis and Aurélien Bellet and Marc Tommasi .
PhD in progress: Brij Srivastava , Representation Learning for Privacy-Preserving Speech Recognition, since Oct 2018 Aurélien Bellet and Marc Tommasi and Emmanuel Vincent .
PhD in progress: Mahsa Asadi , On Decentralized Machine Learning, since Oct 2018. Aurélien Bellet and Marc Tommasi .
PhD in progress: Nicolas Crosetti , Privacy Risks of Aggregates in Data Centric-Workflows, since Oct 2018. Florent Capelli and Sophie Tison and Joachim Niehren and Jan Ramon .
PhD in progress: Robin Vogel , Learning to rank by similarity and performance optimization in biometric identification, since 2017 (CIFRE thesis with IDEMIA and Télécom ParisTech). Aurélien Bellet , Stéphan Clémençon and Anne Sabourin .

Juries

Aurélien Bellet was member of the PhD jury of Guillaume Papa (Télécom ParisTech), Wenjie Zheng (Sorbonne Université), Michael Blot (Sorbonne Université).
Marc Tommasi was member of the Phd jury of Gaëtan Hadjeres (Rapporteur), Alexandre Bérard (Head), Olivier Ruas (Rapporteur), Valentina Zantedeschi.
Pascal Denis was rapporteur on the Phd jury of Elena Knyazeva, Université Paris-Saclay.
Mikaela Keller was member of the recruitment committee for Assistant Professors in Computer Science at Université of Lille and at Université de St-Étienne.
Mikaela Keller was member of the Phd jury of Damien Fourure (Université de St-Étienne) and of the HDR jury of Renaud Lopes (CHRU Lille).
Rémi Gilleron was head of the PhD jury of Romain Warlop (Université de Lille).
Pascal Denis was a member of hiring committee for Junior Research Scientist at Inria Lille.
Marc Tommasi was member of the recruitment committee Assistant Professors in Computer Science at Université of Lille and for professor position at INSA de Lyon.

Previous |

Home | Next next