Statistics at UC Berkeley

Aditya Guntuboyina, Department of Statistics, UC Berkeley
Sep 22, 2014 3:00pm
Abstract:
The least squares estimator in shape constrained regression problems such as isotonic and convex regression automatically adapts to some natural underlying sparsity. I will talk about these results and, in the process, describe some aspects of a general theory for the estimation of a normal mean under convexity constraints. I will also explain connections to the classical random...
NCD Seminar
Stefano DellaVigna, UC Berkeley (Speaker - Featured)
Sep 23, 2014 11:00am
Abstract:
with Susan Athey
Fraydoun Rezakhanlou, UC Berkeley (Speaker)
Sep 23, 2014 3:30pm
Abstract:
As a classical problem in Statistical Mechanics, consider an infinite one-dimensional chain of harmonic oscillators that are interacting via a repulsive potential. Macroscopically, the density functions for mass, momentum and energy satisfy the Euler Equation. By adding noise to the system we may violate some of the conservation laws and simplify the corresponding macroscopic equations. I present...
From Harmonic Oscillators to Kardar-Parisi-Zhang Equation IV
Oskar Hallatschek, UC Berkeley (Speaker)
Sep 24, 2014 1:00pm
Abstract:
The spreading of evolutionary novelties across populations is the central element of adaptation. Unless population are well-mixed (like bacteria in a shaken test tube), the spreading dynamics not only depends on fitness differences but also on the dispersal be- havior of the species. Spreading at a constant speed is gener- ally predicted when dispersal is sufficiently short-ranged, specifically...
Sourav Chatterjee, Stanford University
Sep 24, 2014 3:10pm
Abstract:
Classical large deviations theory is mainly a linear theory. This is demonstrated by the fact that there are no ready-to-use classical tools that can handle large deviations for even the simplest nonlinear functionals, such as triangles in random graphs. In this talk I will present a new theory whose long-term goal is to extend large deviations to the nonlinear setting. The current version of...

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.