Neyman Seminar

The Neyman seminar is the statistics seminar in the Department. Historically, it has been focused on applications of Statistics to other fields. Nowadays, it has a very broad scope, with topics ranging from applications of statistics to theory.

The seminar is held on Wednesdays from 4 to 5 in the Jerzy Neyman room, 1011 Evans.

Details of individual seminar events are published in the campus' event system.

You can sign up to the department's seminars@stat mailing list to receive related announcements.

Add this series of events to your calendar: ICAL or XML

Recent & Upcoming Neyman Seminars

Sam Hopkins, UC Berkeley
Feb 27, 2019 4:00pm
1011 Evans Hall
Abstract:
We study polynomial time algorithms for estimating the mean of a heavy-tailed multivariate random vector. We assume only that the random vector X has finite mean and covariance. In this setting, the radius of confidence intervals achieved by the empirical mean are large compared to the case that X is Gaussian or sub-Gaussian. We offer the first polynomial time algorithm to estimate the mean with...
David Madigan, Columbia University
Mar 6, 2019 4:00pm
1011 Evans Hall
Abstract:
In practice, our learning healthcare system relies primarily on observational studies generating one effect estimate at a time using customized study designs with unknown operating characteristics and publishing – or not – one estimate at a time. When we investigate the distribution of estimates that this process has produced, we see clear evidence of its shortcomings, including an apparent...
Brent Durbin, Smith College
Mar 13, 2019 4:00pm
1011 Evans Hall
Abstract:
Despite more than 20 years of increasing reliance on data-intensive digital tools for commerce, governance, and social interaction, society has been slow to respond to both the promise and the perils of the phenomenon we now call Big Data. This lack of adaptation to new ways of collecting, storing, and analyzing data has been especially apparent within universities and the public sector, both of...
Shankar Iyer, Facebook
Mar 20, 2019 4:00pm
1011 Evans Hall
Abstract:
After a natural disaster or other crisis, humanitarian organizations need to know where affected people are located and what resources they need. While this information is difficult to capture quickly through conventional methods, aggregate usage patterns of social media apps like Facebook can help fill these information gaps. In this talk, I'll describe the data and methodology that power...
Julia Palacios, Stanford University
Apr 2, 2019 4:00pm
141 McCone Hall
Abstract:
In this talk I will present the Tajima coalescent, a model on the ancestral relationships of molecular samples. This model is then used as a prior model on unlabeled genealogies to infer evolutionary parameters with a Bayesian nonparametric method. I will then show that conditionally on observed data and a particular mutation model, the cardinality of the hidden state space of Tajima’s...
Peter Song, University of Michigan
Apr 10, 2019 4:00pm
1011 Evans Hall
Abstract:
I will present a new statistical paradigm for the analysis of streaming data based on renewable estimation and incremental inference in the context of generalized linear models. Our proposed renewable estimation enables us to sequentially update the maximum likelihood estimation and inference with current data and summary statistics of historic data, but with no use of any historic raw data...
Tamara Greasby, The Trade Desk
Apr 17, 2019 4:00pm
1011 Evans Hall
Abstract:
Everyone has had that one ad for that one pair of shoes seem to follow them everywhere they go on the internet. Why does that happen? Especially if you already bought the shoes? To make sense of this, it's worth understanding how marketers have historically measured ad effectiveness -- and why the problem is harder than it seems. Beyond improvements in measuring ad effectiveness, this talk with...