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Adaptation in log-concave density estimation

Presented by: 
Arlene Kim Sungshin Women’s University
Date: 
Tuesday 13th February 2018 - 11:00 to 12:00
Venue: 
INI Seminar Room 2
Abstract: 
The log-concave maximum likelihood estimator of a density on R^d on a sample of size n is known to attain the minimax optimal rate of convergence up to a log factor when d = 2 and d = 3. In this talk, I will review the univariate adaptation result, and will present new results on adaptation properties in the multivariate setting. This is based on joint work with Oliver Feng, Aditya Guntuboyina and Richard Samworth



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University of Cambridge Research Councils UK
    Clay Mathematics Institute London Mathematical Society NM Rothschild and Sons