Learning Determinantal Point Processes

Learning Signed Determinantal Point Processes through the Principal Minor Assignment Problem, Accepted at NIPS 2018 (to come soon on ArXiV)

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, to appear in ESAIM: Probability and Statistics (arXiv:1404.6224)

Uniform behaviors of random polytopes under the Hausdorff metric, to appear in Bernoulli (arXiv:1503.0154)

Concentration of the empirical level sets of Tukey’s halfspace depth, to appear in Probability Theory and Related Fields (arXiv:1605.09456)

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 (Work presented at JSM 2017: Slides)

Methods for Estimation of Convex Sets, to appear in Statistical Science (arXiv:1709.03137)



Best Arm identification for Contaminated Bandits, Joint with J. Altschuler and A. Malek, Submitted (arXiv:1802.09514)