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2023-08-02
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2018-03-23
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2017-09-06
2016-08-15
2016-04-06
2016-03-05
2016-01-14
I am now Adjunct Professor at Laval University, Quebec
2023-04-24
Regions of Reliability in the Evaluation of Multivariate Probabilistic Forecasts has been accepted at ICML 2023
2023-01-21
DAG Learning on the Permutahedron has been accepted at ICLR 2023
2022-09-01
On Margins and Generalisation for Voting Classifiers has been accepted at NeurIPS 2022
2022-08-01
moved to Montreal and joined ServiceNow Research
2021-09-28
Learning Stochastic Majority Votes by Minimizing a PAC-Bayes Generalization Bound has been accepted at NeurIPS 2021
2021-06-05
excited to mentor FDL-Europe's on-board ML challenge this summer!
2021-01-01
moved to London and joined UCL, INRIA-London
2021-05-08
Learning Binary Trees by Argmin Differentiation was accepted at ICML 2021
2020-08-09
I am speaking at the AI and Space panel at WAI global submit
2019-05-10
excited to join the FDL-Europe this summer!
2019-04-20
I was awarded with the "Prix de Thèse" from the French Society for AI
2019-02-01
I was awarded with the "Prix Excellence Doctorat" from the Université Jean Monnet
2018-12-18
I defended my PhD thesis, entitled "A unified view of local learning: theory and algorithms for enhancing linear models"
2018-12-07
"Communication-Efficient Decentralized Boosting while Discovering the Collaboration Graph" presented at MLPCD 2 NeurIPS Workshop
2018-03-23
Adversarial Robustness Toolbox is now available on github
2017-10-24
2017-09-06
our work on adversarial examples will be presented at AISec2017
2016-08-15
2016-04-06
the paper Lipschitz Continuity of Mahalanobis Distances and Bilinear Forms, co-written with R.Emonet and M.Sebban, is now available on arxiv
2016-03-05
2016-01-14
talk on c2lm at Lives ANR project kick-off at Univ. Marseille
View my profileSoftware Development
- I am the creator and a contributor of Adversarial Robustness Toolbox.
Talks
- 2023-04-07 Invited talk at Statlearn'23
Voting classifiers: generalization and optimization
slides - 2023-01-24 Guest Lecture - UCL Machine Learning module
Learning Binary Trees by Continuous Optimization - 2020-09-08 Invited Talk and Panel at Space and AI, WAI global summit
Machine Learning with Earth Observational data - 2020-08-14 Oral Presentation at FDL - results showcase
Towards a Digital Twin of the Earth - 2020-04-29 Invited Talk at ICLR-CCAI 2020
CUMULO: A Dataset for Learning Cloud Classes
slides, talk - 2019-12-14 Spotlight Talk at CCAI 2019, Vancouver
CUMULO: A Dataset for Learning Cloud Classes
slides, talk, poster - 2019-08-16 Oral Presentation at FDL - results showcase, Oxford
Semi-Supervised Cloud Classification - 2019-07-04 Oral Presentation at the AFIA Award Ceremony, Toulouse
for best PhD dissertation 2019
A unified view of local learning: theory and algorithms for enhancing linear models - 2018-09-11 Oral Presentation at ECML2018, Dublin
Fast and Provably Effective Multi-view Classification with Landmark-based SVM
slides - 2018-06-20 Oral Presentation at Cap2018, Rouen
Decentralized Frank-Wolfe Boosting for Collaborative Learning of Personalized Models
slides - 2017-11-17 Oral Presentation at Grehack2017, Grenoble
Efficient Defenses Against Adversarial Attacks
slides, talk - 2017-04-10 Seminar at Magnet team, INRIA Lille
a New Surrogate Risk for Learning from Weakly Labeled Data
slides - 2016-06-02 PhD Seminar at Lab. H.Curien, Saint-Etienne
Surrogate Loss Functions as Bregman Divergences
slides - 2016-01-14 Lives ANR project kick-off meeting at Univ. Marseille
Metric Learning as Convex Combination of Local Models with Generalization Guarantees
slides - 2014-09-03 Master Seminar at Lab. H.Curien, Saint-Etienne
Statistical Classification with Fisher Kernel
slides
Research Experience
- Summer 2021
Research Mentor at Frontier Development Lab, Europe
Change detection onboard satellites - Summer 2020
Research Scientist at Frontier Development Lab, Europe
Data-driven global precipitation forecasting - Summer 2019
Research Scientist at Frontier Development Lab, Europe, mentored by Matt Kusner and Duncan Watson-Parris
Atmospheric Phenomena and Climate Variability challenge - September 2017
Visiting Researcher at INRIA, Lille, collaborating with Marc Tommasi and Aurélien Bellet
decentralized learning of personalized models exploiting information of a graph of users - May-August 2017
Research Intern at IBM Research, Dublin, supervised by Mathieu Sinn and Maria-Irina Nicolae
studying and building Deep Learning architectures robust to adversarial examples - Avril-September 2015 MSc Thesis at Lab. H.Curien, Saint-Etienne, supervised by R.Emonet and M.Sebban
Local Metrics learning and combination for color distance estimation - May-September 2014 Master Intern at Lab. H.Curien, Saint-Etienne, supervised by R.Emonet and M.Sebban
Fisher Kernels in temporal probabilistic models for classification
Research Projects
- My postdoc was funded by APRIORI ANR project (A PAC-Bayesian Representation Learning Perspective)
- My PhD was funded by Solstice ANR project (Similarity Of Locally Structured Data in Computer Vision)
- I actively participated in Lives ANR project (Learning with Interactive ViEwS)
Teaching Assistance
- 2017-2018
- 1M: Design and Analysis of Algorithms (18h)
- 2016-2017
- 1B: Introduction to Computer Science (32h)
- 2B: Imperative Programming in Python (20h)
- 1M: Design and Analysis of Algorithms (18h)
- 1M: Data Analysis (18h)
- 1M: Introduction to Machine Learning (5h)
- 2015-2016
- 1B: Introduction to Computer Science (32h), Introduction to Latex, Excel, Bash (36h)
- 1M: Machine Learning-Ensemble Methods (2h)
Organizations
- 2018-2019 organizer of the reading groups of the Data Intelligence group at Lab. H.Curien, Saint-Etienne
- 2018 member of the program committee of Nemesis 2018 workshop
- 2018 co-organizer of the closing seminar of SOLSTICE project
- 2015-2016 co-organizer of the PhD Seminars of Data Intelligence group at Lab. H.Curien, Saint-Etienne