Publications

Learning on metric spaces and Riemannian manifolds

Finite sample bounds for barycenter estimation in geodesic spaces, Joint with Jordan Serres (submitted)

A generalization of Grünbaum’s inequality in RCD(0,N) spaces, Joint with Shin-ichi Ohta and Jordan Serres, Journal of Functional Analysis, Vol. 290(1) (2025)

Convex generalized Fréchet means in a metric tree, Joint with Gabriel Romon (submitted)

Concentration of empirical barycenters in metric spaces, Joint with Jordan Serres, Algorithmic Learning Theory (2024)

Geodesically convex M-estimation in metric spaces, Conference On Learning Theory 2023

Learning Determinantal Point Processes

Recovering a Magnitude-Symmetric Matrix from its Principal Minors, Joint with J. Urschel, Linear Algebra and Applications, Vol. 703, pp. 232-267 (2024)

Scalable Learning and MAP Inference for Nonsymmetric Determinantal Point Processes, Joint with M. Gartrell, I. Han, E. Dohmatob and J. Gillenwater, International Conference on Learning Representations 2020 (arXiv2006.09862)

Learning Non Symmetric Determinantal Point Processes, Joint with M. Gartrell, E. Dohmatob and S. Krichene, NeurIPS 2019 (arXiv1905.12962)

Learning Signed Determinantal Point Processes through the Principal Minor Assignment Problem, NIPS (2018) (arXiv:1811.00465; For the presentation: Poster)

Maximum likelihood estimation of Determinantal Point Processes, Joint with A. Moitra, P. Rigollet and J. Urschel (arXiv:1701.06501)

Learning Determinantal Point Processes with Moments and Cycles, Joint with A. Moitra, P. Rigollet and J. Urschel, ICML (2017) (For the presentation: Slides – Poster)

Rates of estimation for determinantal point processes, Joint with A. Moitra, P. Rigollet and J. Urschel, COLT (2017) (For the presentation: Slides – Poster)

Set estimation / Stochastic geometry

Adaptive estimation of convex polytopes and convex sets from noisy data, Electronic Journal of Statistics, Vol. 7, pp. 1301-1327 (2013)

Adaptive estimation of polytopal and convex support, Probability Theory and Related Fields, Vol. 164, pp. 1-16 (2016)

A change-point problem and inference for segment signals, ESAIM: Probability and Statistics, Vol. 22, pp. 210-235 (2018)

Uniform behaviors of random polytopes under the Hausdorff metric, Bernoulli, Vol. 25, pp. 1770-1793 (2019)

Concentration of the empirical level sets of Tukey’s halfspace depth, Probability Theory and Related Fields, Vol. 173, pp. 1165-1196 (2019)

Deviation inequalities for random polytopes in arbitrary convex bodies, Bernoulli 26(4), pp. 2488-2502 (2020) (arXiv:1704.01620)

Estimation of convex supports from noisy measurements, Joint with J. Klusowski and X. Yang, Bernoulli 27(2), pp. 772-793 (2021) (arXiv:1804.09879)

Methods for Estimation of Convex Sets, Statistical Science, Vol. 33, pp. 615-632 (2018)

Robustness/Privacy

Best Arm identification for Contaminated Bandits, Joint with J. Altschuler and A. Malek, Journal of Machine Learning Research, Vol. 20 (2019) (arXiv:1802.09514)

A nonasymptotic law of iterated logarithm for robust online estimators, Joint with A. Dalalyan and N. Schreuder, Accepted at AISTATS 2020 (arXiv:1903.06576)

Differentially Private Sub-Gaussian Location Estimators, Joint with M. Avella, Submitted (arXiv:1906.11923)

Propose, Test and Release: Differentially Private Estimation with High Probability, Joint with M. Avella, Submitted (arXiv:2002.08774)

Miscellaneous

On the continuity of geodesically convex functions on Riemannian manifolds, Joint with P. Pansu (arXiv:2512.05621)

Asymptotics of constrained M-estimation under convexity, Submitted (arXiv:2511:04612)

Bayesian Off-Policy Evaluation and Learning for Large Action Spaces, Joint with I. Aouali, A. Korba and D. Rohde, Artificial Intelligence and Statistics (AISTATS) (2025)

Unified PAC-Bayesian Study of Pessimism for Offline Policy Learning with Regularized Importance Sampling, Joint with I. Aouali, A. Korba and D. Rohde, Proceedings of the 40th conference on Uncertainty in Artificial Intelligence (UAI), pp. 88-109 (2024)

Exponential smoothing for off-policy learning, Joint with I. Aouali, A. Korba and D. Rohde, International Conference in Machine Learning (ICML) (2023)

Learning rates for Gaussian mixtures under group invariance, Proceedings of the 32nd Conference On Learning Theory (COLT), pp. 471-491 (2019) 

Statistical Guarantees for Generative Models without Domination, Joint with N. Schreuder and A. Dalalyan, Proceedings of Algorithmic Learning Theory (ALT), pp. 1051-1071 (2021)