## Learning Determinantal Point Processes

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

Learning Signed Determinantal Point Processes through the Principal Minor Assignment Problem, *Accepted at 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, *Submitted *(arXiv:1701.06501)

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

Rates of estimation for determinantal point processes, Joint with A. Moitra, P. Rigollet and J. Urschel, Accepted at 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 universal deviation inequality for random polytopes, Working paper (__arXiv:1311.2902__)

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)

Uniform deviation and moment inequalities for random polytopes with general densities in arbitrary convex bodies, *Submitted *(arXiv:1704.01620)

Estimation of convex supports from noisy measurements, Joint with J. Klusowski and X. Yang, *Submitted* (arXiv:1804.09879)

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

## Robustness

Best Arm identification for Contaminated Bandits, Joint with J. Altschuler and A. Malek, *Accepted for publication at Journal of Machine Learning Research* (arXiv:1802.09514)

A nonasymptotic law of iterated logarithm for robust online estimators, Joint with A. Dalalyan and N. Schreuder, *Submitted *(arXiv:1903.06576)

## Miscellaneous

Differentially Private Sub-Gaussian Location Estimators, Joint with M. Avella, *Submitted*

Learning rates for Gaussian mixtures under group invariance, *Accepted at *the Conference On Learning Theory (COLT) 2019 (arXiv:1902.11176)