Some talks:

YearTitle EventSlides/Video
2021Supervised learning with missing values (pres of neural networks with missing values) IAS Special Year on Optimization, Statistics & Theoretical Machine Learning slides
2021Introduction to causal inferenceSeminar Montpellier ML, Gustave Roussy, Google Brainslides
2019 Doubly-robust treatment effect estimation with incomplete confoundersSeminar Frejus I. Mayer.slides
2019Decisions trees with missing values, selection and predictionSFDS N Prost. slides
2019On the consistency of supervised learning with missing valuesCornell, Statlearn, Google Brainslides
2019 High dimensional variable selection with missing values with adaptive slopeDagStat, Munichslides
2019Low-rank estimation and imputation with MNAR data DagStat, Munichslides
2019Causal inference with missing valuesLyonslides
2018Distributed multilevel matrix completion for medical dataFrance-Finland Worshop, Washington University Seminarslides
Stochastic Approximation EM for logistic regression with missing valuesCMStat, London, 17 Decemberslides
2017Single Imputation with data depthCMStat, London, 17 Decemberslides
2017 R forwards to widen the participation of under-represented groupsuseR!2017, 7 Julyvideo
2017Empirical Bayes approaches to PageRank type algorithms for rating scienti fic journals French Stat Society, 29 Mayslides
2017Low-rank log-linear models. Vienna, University of economics and business, 16 March
Telecom, Paris, 23 March.
2016 Meetup Machine Learning, Paris, France, 10 February
2016 Imputation with data depth - Pavlo Mozharovskyi French Stat Society, Montpellier, France, May slide
2016MultiLogit bilinear model & MCA Working group on model based clustering, Paris, France, 22 July
AgroPariTech, Paris, France, 13 June
2015Missing values and principal components methods INRIA, Orsay, France, 12 October
Tesla Motor, Palo Alto, USA, 14 August
2015Multiple imputation for categorical data Conference CARME (correspondence analysis & related methods), Napoli, Italy, 21 September
Journée de Statistiques, Rennes, France, 23 october
20152015 A flexible framework for regularized low rank matrix estimationLos Alamos, USA, 15 February
Rotterdam University , Netherlands, 30 January
Adobe Research , San Jose, USA, 20 January
2015 Visualization with regularized PCA Stanford Biostatistics, Palo Alto, USA, 15 January
MultiLogit bilinear model & MCAslides
Bootstrap approach for low rank estimationslides
A missing values tour with principal componentsslides
Visualization with regularized PCA and confidence ellipses

Exploratory data analysis: multi­-blocks/3ways methodsslides
Multiple imputation for categorical dataslides
Imputation of mixed data: Random forest/PCAslides
2014A flexible framework for regularized low rank matrix estimation Montpellier 2 University, France, 20 October
Paris Descartes University, France, 24 October
Wroclaw University, Poland, 31 October