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Exact Solutions in Log-Concave Maximum Likelihood Estimation

  • Miruna-Stefana Sorea (MPI MiS, Leipzig)
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Abstract

We study probability density functions that are log-concave. Despite the space of all such densities being infinite-dimensional, the maximum likelihood estimate is the exponential of a piecewise linear function determined by finitely many quantities, namely the function values, or heights, at the data points. We explore in what sense exact solutions to this problem are possible. Joint work with Alexandros Grosdos, Alexander Heaton, Kaie Kubjas, Olga Kuznetsova, and Georgy Scholten.

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seminar
3/17/20 2/21/22

Nonlinear Algebra Seminar Online (NASO)

MPI for Mathematics in the Sciences Live Stream

Katharina Matschke

MPI for Mathematics in the Sciences Contact via Mail