Introduction to Federated Learning
Efficient Differentially Private Averaging with Trusted Curator Utility and Robustness to Malicious Parties
Invited talk at Google Workshop on Federated Learning and Analytics, virtual event, 2020.
Grand débat et IA : quelle transparence pour le traitement des données ? Une tentative de rétro-ingénierie de la synthèse
Contributed talk at Journées d'étude "Quels outils d'analyse pour les gilets jaunes ?", Sciences Po Paris, 2020.
Fully Decentralized Joint Learning of Personalized Models and Collaboration Graphs
Seminar at Criteo AI Labs Paris, 2020.
Invited talk at Google Workshop on Federated Learning and Analytics, 2019.
Invited talk at the workshop Graph signals: learning and optimization perspectives, 2019.
Invited talk at the workshop The power of graphs in machine learning and sequential decision making, 2019.
Invited talk at the Applied Machine Learning Days, 2020.
Invited talk at the CIRM Conference on Optimization for Machine Learning, 2020.
Invited talk at the International Workshop on Distributed Cloud Computing, 2020.
Artificial Intelligence & Privacy Protection
Collaborative Machine Learning in Large-Scale Peer-to-Peer Distributed Systems
Seminar at Inria WIDE, 2018.
Invited talk at the 4th GDR RSD and ASF Winter School on Distributed Systems and Networks, 2019.
Who started this rumor? Quantifying the natural differential privacy guarantees of gossip protocols
Talk at the Workshop on Privacy-Aware Distributed Machine Learning , 2018.
Seminar at Inria Sequel, Inria Multispeech, CMLA, Naver Labs Europe, Alan Turing Institute, Thales Research & Technology and Miles Paris Dauphine, 2017-2019.
Invited talk at the 2nd Russian-French Workshop in Big Data and Applications, 2017.
Invited talk at the EPFL-Inria Workshop, 2018.
Invited talk at the Journées de Statistique (session SSFAM), 2018.
Invited talk at the CIFAR-UKRI-CNRS workshop on AI & Society: From principles to practice, 2019.
Invited talk at the International Workshop on Machine Learning & Artificial Intelligence, 2019.
A Massively Distributed Algorithm for Private Averaging with Malicious Adversaries
Seminar at CRIStAL Lille (DaTinG department day), Statistics Seminar of Paris 6/7 and LTCI Télécom Paris, 2017-2018.
Invited talk at the DALI 2017 Workshop on Fairness and Privacy in Machine Learning, 2017.
Seminar at Inria Magnet and LPD Lab - EPFL, 2016-2017.
Invited talk at the Workshop on Distributed Machine Learning (Télécom Paris), 2016.
Invited talk at the Journée Apprentissage et Interactions du GdR IA (UPMC), 2017.
Scaling-up Empirical Risk Minimization: Optimization of Incomplete U-statistics
Invited talk at the International Workshop on Machine learning, Optimization and Big Data (MOD 2015), 2015.
The Frank-Wolfe Algorithm: Recent Results and Applications to High-Dimensional Similarity Learning and Distributed Optimization
Seminar at LIP6 UPMC, LaHC Saint-Étienne, Heudiasyc Compiègne, LIF Marseille, Inria Magnet, LIG Grenoble, CEREMADE Paris Dauphine, IMT Toulouse, LRI Inria/Paris Sud, AgroParisTech, Séminaire Parisien de Statistique and ENS/Inria Paris, 2014-2015.
Invited talk at ICML 2015 workshop "Greed is Great", 2015.