Statistics at UC Berkeley

Tyler Helmuth, U.C. Berkeley Mathematics
May 3, 2017 3:10pm 1011 Evans Hall
Abstract:
The lace expansion is one of the primary tools for proving that probability models in high dimensions have mean field behaviour. I will explain the previous sentence by describing joint work in progress with David Brydges and Mark Holmes in which we develop a continuous time lace expansion. Our method allows us to analyze n-component field theories when n is zero, one, or two. The case n=2 is new.
Mikhail Belkin, Department of Computer Science and Engineering, Ohio State University
May 3, 2017 4:00pm 1011 Evans Hall
Abstract:
What can we learn from big data? First, more data allows us to more precisely estimate probabilities of uncertain outcomes. Second, data provides better coverage to approximate functions more precisely. I will argue that the second is key to understanding the recent success of large scale machine learning. A useful way of thinking about this issue is that it is necessary to use many more...

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.