Statistics at UC Berkeley

Allan Sly, Princeton University
Jan 24, 2020 12:10pm 1011 Evans Hall
Replica Symmetry Breaking for Random Regular NAESAT Ideas from physics have predicted a number of important properties of random constraint satisfaction problems such as the satisfiability threshold and the free energy (the exponential growth rate of the number of solutions). Another prediction is the condensation regime where most of the solutions are contained in a small number of clusters...
Moritz Voss, UCSB
Jan 28, 2020 11:00am 1011 Evans Hall
ABSTRACT: We study the competition of two strategic agents for liquidity in the benchmark portfolio tracking setup of Bank, Soner, Voss (2017), both facing common aggregated temporary and permanent price impact à la Almgren and Chriss (2001). The resulting stochastic linear quadratic differential game with terminal state constraints allows for an explicitly available open-loop Nash...
Alexander Volberg, Michigan State University
Jan 29, 2020 3:10pm 330 Evans Hall
We improve the constant $\frac{\pi}{2}$ in $L^1$-Poincar\'e inequality on Hamming cube. For Gaussian space the sharp constant in $L^1$ inequality is known, and it is the square root of $\frac{\pi}{2}$ (Maurey—Pisier). For Hamming cube the sharp constant is not known, and the square root of $\frac{\pi}{2}$ gives an estimate from below for this sharp constant. On the other hand, Ben Efraim and...
Tim Sullivan, Freie Universität Berlin and Zuse Institute Berlin
Jan 29, 2020 4:00pm 1011 Evans Hall
Numerical computation --- such as numerical solution of a PDE, or quadrature --- can modelled as a statistical inverse problem in its own right. In particular, we can apply the Bayesian approach to inversion, so that a posterior distribution is induced over the object of interest (e.g. the PDE's solution) by conditioning a prior distribution on the same finite information that would be used in a...
Neyman Seminar
Saad Mouti, UC Berkeley
Feb 4, 2020 11:00am 1011 Evans Hall

Statistics at UC Berkeley: We are a community engaged in research and education in probability and statistics. In addition to developing fundamental theory and methodology, we are actively involved in statistical problems that arise in such diverse fields as molecular biology, geophysics, astronomy, AIDS research, neurophysiology, sociology, political science, education, demography, and the U.S. Census. We have forged strong interdisciplinary links with other departments and areas of study, particularly biostatistics, mathematics, computer science, and biology, and actively seek to recruit graduate students and faculty who can help to build and maintain such links. We also offer a statistical consulting service each semester.