**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.

# Statistics at UC Berkeley

Nov 16, 2017

Oct 27, 2017

Oct 24, 2017

Shirshendu Ganguly, UC Berkeley

Abstract:

Statistical mechanics models are ubiquitous at the interface of probability theory, information
theory, and inference problems in high dimensions. In this talk, we will focus on
sparse networks, and polymer models on lattices. The study of rare behavior (large deviations)
is intimately related to the understanding of such models. In particular, we will
consider the rare events that a sparse...

Shirshendu Ganguly, UC Berkeley

Abstract:

Statistical mechanics models are ubiquitous at the interface of probability theory, information
theory, and inference problems in high dimensions. In this talk, we will focus on
sparse networks, and polymer models on lattices. The study of rare behavior (large deviations)
is intimately related to the understanding of such models. In particular, we will
consider the rare events that a sparse...

Speaker: Mariana Olvera-Cravioto, UC Berkeley (Speaker - Featured)

Abstract:

The talk will center around a set of recent results on the analysis of Google’s PageRank algorithm on directed complex networks. In particular, it will focus on the so-called power-law hypothesis, which states that the distribution of the ranks produced by PageRank on a scale-free graph (whose in-degree distribution follows a power-law) also follows a power-law with the same tail-index as the...

Jacob Steinhardt, Stanford University

Abstract:

Deployed machine learning systems create a new class of computer security vulnerabilities
where, rather than attacking the integrity of the software itself, malicious actors exploit the
statistical nature of the learning algorithms. For instance, attackers can add fake training data,
or strategically manipulate input covariates at test time.
Attempts so far to defend against these...

Merle Behr, University of Göttingen

Abstract:

A challenging problem in cancer genetics is that tumors often consist of a few different groups of cells, so called clones, where each clone has different mutations, like copy-number (CN) variations. In whole genome sequencing the mutations of the different clones get mixed up, according to their relative unknown proportion in the tumor. However, CN's of single clones can only take values in a...