Marco Cuturi

Research Interests: machine learning, optimal transport, optimization, time-series, kernels.

Contact

Access

The Apple Paris office is close to the Palais de Tokyo. ENSAE is in the IP Paris, right next to Ecole Polytechnique.

Upcoming Events

Recent News

07-Dec-22 Séminaire Palaisien
24-Oct-22 OT and Applications, SNS Pisa
19-Oct-22 ScaDS-AI seminar, Leipzig
28-Sep-22 SIAM MDS, Tutorial, San Diego
6-Sep-22 EURANDOM, Workshop on OT/Stats/ML, Eindhoven
16-May-22 Applied OT, IMSI
30-May-22 PDE Methods in Data Science and Machine Learning, Fields
28-Jun-22 IMS Meeting, OT Workshop, London
12-Aug-22 Machine learning and PDEs: theory, algorithms, and its applications, Postech, Seoul
02-Mar-22 MIA, Broad Institute
17-Jan-22 Zinal Winter School
01-Sep-21 Simmons Geometric Methods Bootcamp, Berkeley
04-Aug-21 MLSS Taipei
15-Jun-21 Conf. Apprentissage Automatique, St Etienne
29-Mar-21 Biostats Department Seminar, JHU
18-Mar-21 Bocconi Stats Seminar, Milano
24-Feb-21 Linköping University ML Seminar
16-Sep-20 talk at Riken
10-Sep-20 GAMM Workshop, Leipzig
04-Jul-20 SGP’20 Graduate School, Utrecht
02-Jul-20 MLSS Tübingen
13-Dec-19 Optimal Transport and Machine Learning Workshop 2019 @ Neurips 2019, Vancouver
19-Nov-19 spoke @ CORE Seminar, U. Washington, Seattle
16-Nov-19 spoke @ Optimization-Conscious Econometrics Conference, U. Chicago
15-Nov-19 spoke @ Optimization Seminar, Fields Institute, Toronto
14-Nov-19 spoke @ Math and Data NYU Seminar, NYU
06-Nov-19 spoke @ Statistics with Geometry and Topology, Toulouse
28-Oct-19 spoke @ Computational Harmonic Analysis and Data Science, Oaxaca
18-Oct-19 spoke @ FAST Global Innovation Forum, Yerevan
02-Oct-19 spoke @ ML in the real world, Criteo, Paris
05-Sep-19 slides for DALI Theory, Alg. and Comp. of Modern Learning Sys., San Sebastian
05-Sep-19 slides for DALI Geometric Deep Learning, San Sebastian
29-Aug-19 Spoke @ Structural Inference in High-Dimensional Models, HSE, St Petersburg
26-Aug-19 slides for MLSS in Skoltech, Moscow
31-Jul-19 Spoke @ Discrete Optimization and Machine Learning, Tokyo
23-Jun-19 Spoke @ People in Optimal Transportation and Applications, Cortona
13-Jun-19 Spoke @ Geometric and Topological Approaches to Data Analysis, Cambridge, UK
17-May-19 Spoke @ IST Young Scientist Symposium, Vienna
13-May-19 Spoke @ Optimal transport: from Geometry to Numerics, Vienna
09-May-19 slides given at the Introductory School on OT, Vienna
01-Apr-19 Imaging & ML, Paris
25-Mar-19 Les Houches Optimization and Statistical Learning
09-Jan-19 Slides for my MLSS South Africa presentation.
26-Nov-18 Slides at Bayesian statistics in the big data era
12-Nov-18 Slides presented at Optimal Transportation and Applications, Pisa
01-Oct-18 Joined Google brain in Paris.
17-Sep-18 spoke at Workshop ML and AI, Telecom ParisTech
13-Sep-18 Spoke at ICMS Workshop, Gradient flows: challenges and new directions, Edinburgh
05-Sep-18 Slides for my presentation at Structural Inference in High Dimensional Models, Moscow
28-Jun-18 Gave tutorial at Data Science Summer School at Palaiseau
18-Jun-18 My Slides at MLSS Buenos Aires
15-Jun-18 Spoke at Seminario de Probabilidad y Estadistica, Universidad de la Republica, Montevideo
11-Jun-18 Spoke at The Interplay between Statistics and Optimization in Learning, Alan Turing Institute, London
04-Jun-18 Spoke at Mass Transportation Theory: Opening perspectives in Statistics, Probability and Computer Science, IMUVa, Valladolid
28-May-18 Slides at 50ème Journées SFdS, Saclay
25-May-18 Spoke at CSML Seminar, UCL, London
17-May-18 Spoke at Orsay Maths Dept seminar
14-May-18 Spoke at Séminaire AgroParisTech, Paris
26-Apr-18 TWiMLAI Interview about our NIPS Tutorial
12-Avr-18 Slides for my seminar at ENS Lyon
27-Mar-18 Spoke at Data Science Spring School, Kyoto
19-Jan-18 Spoke at Statistics/Learning at Paris Saclay, IHES
15-Jan-18 Spoke at Mathematics in Image Analysis 2018, Berlin
09-Dec-17 Optimal Transport and Machine Learning, NIPS 2017 workshop, Long Beach
08-Dec-17 Thanks to Mathieu Blondel for presenting our work on sDTW at the Time Series Workshop, NIPS 2017 workshop, Long Beach
04-Dec-17 Gabriel Peyré and I have released a first draft of our review book on computational OT, comments welcome!
04-Dec-17 Slides in .key, .pdf and .m4v formats of our NIPS tutorial ‘‘A primer on optimal transport’’, (with J. Solomon), Long Beach
30 & 31-Nov-17 Slides in avi or pdf format for my two lectures at PIMS, UBC, Vancouver
06-Nov-17 Mikhail Yurochkin and Nhat Ho have kindly shared python code on Wasserstein barycenters, implementing in particular our ICML’14 paper. See also Marcel Klatt's implementation in R.
28-Oct-17 Slides at ICCV Workshop, Geometry meets deep learning, Venezia
05-Oct-17 Gave a talk at France is AI conference, Paris
21-Sep-17 Thanks to all participants of the France Japan Machine Learning Workshop!
09-Aug-17 Slides for my presentation at ICML, Sydney (Code available).
01-Aug-17 Slides for my presentation at Optimal Transport and Related Topics, KIAS, Seoul
03-Jul-17 Slides for my mini-course at Lectures on OT and ML, KIAS, Seoul
8-Jun-17 Code for sDTW!, thanks to Mathieu Blondel.
22-May-17 Slides at SIOPT Workshop, kindly presented by Francis Bach.
10-May-17 Spoke at Mathematical Statistics Seminar of Weierstrass Institute, Berlin
30-Apr-17 Thanks to participants of Optimal Transport meets Probability, Statistics and Machine Learning, BIRS/CMO
23-Mar-17 Spoke at Statistical Recovery of Discrete, Geometric and Invariant Structures, Oberwolfach
18-Apr-17 Slides for my talk at RIKEN AIP, Tokyo
10-Jan-17 Slides for my talk at Functoriality in Geometric Data workshop, Dagstuhl
17-Dec-16 Spoke at Workshop on statistics, Hiroshima University
9-Dec-16 NIPS Time Series Workshop 2016 was held in Barcelona
13-Nov-16 Spoke at Mathematical Progress in Expressive Image Synthesis, Fukuoka
9-Nov-16 Spoke at PGMO Days, Orsay
26-Sep-16 Spoke at IPAM Workshop, ML meets many particle problems, UCLA
19-Sep-16 Spoke at ECML/PKDD Workshop, Adv. Analytics and Learning on Temporal Data
18-Jul-16 spoke at Computational Optimal Transport, U. Montréal
03-Jun-16 spoke at Korea/Japan ML Symposium, Seoul
07-Apr-16 spoke at Statlearn 2016, Vannes
16-Mar-16 spoke at EECS - BLISS Seminar, UC Berkeley
19-Feb-16 Slides for my Microsoft Research Cambridge talk
04-Dec-15 Slides for ML Tea seminar, MIT
01-Dec-15 Slides for CILVR Seminar, NYU
25-Nov-15 Slides for my IBIS 2015 Workshop presentation.
18-Nov-15 Spoke @ Workshop on Learning, IMS NUS, Singapore
05-Nov-15 Spoke @ Recent Advances in Machine Learning and Applications, Nagoya
28-Oct-15 Spoke @ Germany-Japan Adaptive BCI Workshop, Kyoto
07-Oct-15 Slides for my Workshop on Optimization in machine learning, vision and image processing presentation
18-Sep-15 Slides for my GTC presentation
23-Aug-15 Thanks to the 430 participants of the MLSS’15 in Kyoto! (Pictures)

06-Mar-15 spoke at New Trends in Optimal Transport, Bonn
15-Feb-15 spoke at Advances in Numerical Optimal Transportation workshop, Banff
11-Jan-15 spoke at Optimization and Statistical Learning workshop, Les Houches
18-Dec-14 spoke at Learning Theory Workshop, FoCM, Montevideo
01-Sep-14 co-organizing the NIPS’14 Workshop on Optimal Transport and Machine Learning.
25-Mar-14 Slides and Poster of our ICML’14 paper on Wasserstein barycenters.
25-Mar-14 Consider submitting a tutorial proposal to ACML’14. I will be AC @ NIPS’14.
24-Mar-14 Updated code to compute fast approximations to EMD. Previous version had a bug.
11-Feb-14 For your calendars: Trends in Machine Learning workshop in Kyoto U. on March 17-18!
16-Dec-13 A new version of our preprint Ground Metric Learning is online.
25-Nov-13 My code to compute dual-Sinkhorn divergences is online. Please report any bug.
12-Nov-13 The final version of my paper on Sinkhorn distances is online.
26-Sep-13 Preliminary material to compute Sinkhorn distances, work to be presented at NIPS’13
11-Jul-13 Very excited to give a talk @ workshop on computational OT on Sep. 2 @ IHP, Paris.
27-Jun-13 Slides of our talk at ICML’13 and poster
15-Jan-13 Slides of my lecture at the Machine Learning Tutorial organized by KAIST
15-Sep-12 Many thanks to all the participants of the MLSS’12 Kyoto, what a fantastic two weeks!

24-Jul-12 My slides at the RKHS / Kernel based methods workshop of ICML’12.
9-Apr-12 The Informatics Seminar is starting again this spring semester.
25-Jan-12 Slides for my Nagoya Institute of Technology talk.
11-Jan-12 The application website for the MLSS opens on January 16th! Please check the updated speakers’ list.
12-Oct-11 New preprint: Ground Metric Learning
12-Oct-11 The 21st Machine Learning Summer School will be held next summer in Kyoto University, between August 27th and September 7th 2012. This edition of the MLSS series will take place for the first time in Japan. Our website is still under construction, applications will open later this year.
14-Sep-11 New matlab and python code for alignment kernels
17-Jun-11 My slides for the CCE Dept. Colloquium on June 17th.
15-Jun-11 Arnaud Doucet Slides, June 15th.
22-May-11 The PEMS-SF dataset is available in the UCI Machine Learning Repository. Here is a local copy in .mat format

Vita

I received my Ph.D. in 11/2005 from Ecole des Mines de Paris. Before that I graduated from the ENSAE with a master degree from ENS Cachan. I worked as a post-doctoral researcher at the Institute of Statistical Mathematics, Tokyo, between 11/2005 and 03/2007. Between 04/2007 and 09/2008 I worked in the financial industry. After working at the ORFE department of Princeton University between 02/2009 and 08/2010 as a lecturer, I was at the Graduate School of Informatics of Kyoto University between 09/2010 and 09/2016 as an associate professor (tenured in 11/2013). I have joined ENSAE in 09/2016, working there part-time from 10/2018. Between 10/2018 and 01/2022 I was with the Google Brain team. I joined Apple on 01/2022, working in the Machine Learning Research team led by Samy Bengio.