Liouville quantum gravity from random matrix dynamics

CMSA Room G10 CMSA, 20 Garden Street, Cambridge, MA, United States

Probability Seminar Speaker: Hugo Falconet (Courant Institute, NYU) Title: Liouville quantum gravity from random matrix dynamics Abstract: The Liouville quantum gravity measure is a properly renormalized exponential of the 2d GFF. In this talk, I will explain how it appears as a limit of natural random matrix dynamics: if (U_t) is a Brownian motion on the unitary […]

Outlier-Robust Algorithms for Clustering Non-Spherical Mixtures

Probability Seminar Speaker: Ainesh Bakshi (MIT) Title: Outlier-Robust Algorithms for Clustering Non-Spherical Mixtures Abstract: In this talk, we describe the first polynomial time algorithm for robustly clustering a mixture of statistically-separated, high-dimensional Gaussians. Prior to our work this question was open even in the special case of 2 components in the mixture. Our main conceptual contribution […]

Lipschitz properties of transport maps under a log-Lipschitz condition

Harvard Science Center 1 Oxford Street, Cambridge, MA

Probability Seminar Location: Room 109, Harvard Science Center, 1 Oxford Street, Cambridge MA 02138 Speaker: Dan Mikulincer (MIT) Title: Lipschitz properties of transport maps under a log-Lipschitz condition Abstract: Consider the problem of realizing a target probability measure as a push forward, by a transport map, of a given source measure. Typically one thinks about […]

Fourier quasicrystals and stable polynomials

Harvard Science Center 1 Oxford Street, Cambridge, MA

Probability Seminar Note location change: Science Center Room 300H Speaker: Lior Alon (MIT) Title: Fourier quasicrystals and stable polynomials Abstract: The Poisson summation formula says that the countable sum of exp(int), over all integers n, vanishes as long as t is not an integer multiple of 2 pi. Can we find a non-periodic discrete set A, such […]

Neural Optimal Stopping Boundary

CMSA Room G10 CMSA, 20 Garden Street, Cambridge, MA, United States

Speaker: Max Reppen (Boston University) Title: Neural Optimal Stopping Boundary Abstract:  A method based on deep artificial neural networks and empirical risk minimization is developed to calculate the boundary separating the stopping and continuation regions in optimal stopping. The algorithm parameterizes the stopping boundary as the graph of a function and introduces relaxed stopping rules based on fuzzy […]