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Statistics Department Seminar

The Statistics Seminars for Autumn Quarter will be held in Room 380Y of the Sloan Mathematics Center in the Main Quad at 4:30pm on Tuesdays. Refreshments are served at 4pm in the Lounge on the first floor of Sequoia Hall.

You can receive a weekly announcement of seminar offerings by subscribing to our mailing list at any time! Please follow the link for Statistics Seminars and fill in the fields required to subscribe, unsubscribe, change subscription options, and so on.

We provide a LaTeX template for speakers to use when submitting the abstract for a seminar (sample PDF output). Using this template makes it possible to post the abstract promptly and without unintended errors that might creep in if your text has to be migrated from another source.

Questions about Seminars may be sent to seminars@stat.stanford.edu.

March 2018
Date/Time Speaker Affiliation Title
Tue 13 Mar
04:30PM
Genevera Allen Rice University Inference, computation, and visualization for convex clustering and biclustering
Tue 06 Mar
04:30PM
Daniela Witten University of Washington ---
February 2018
Date/Time Speaker Affiliation Title
Tue 27 Feb
04:30PM
Jelena Bradic UC San Diego ---
Tue 20 Feb
04:30PM
Guillaume Basse Harvard University ---
Tue 13 Feb
04:30PM
Art Owen Stanford Statistics Importance sampling the union of rare events with an application to power systems analysis
Tue 06 Feb
04:30PM
Yuting Wei UC Berkeley Geometric analysis of hypothesis testing and early stopping for boosting
January 2018
Date/Time Speaker Affiliation Title
Tue 30 Jan
04:30PM
Shirshendu Ganguly UC Berkeley Understanding rare events in models of statistical mechanics
Thu 25 Jan
04:00PM
Extra Seminar
Roy Lederman Princeton University Inverse problems and unsupervised learning with applications to cryo-electron microscopy
Tue 23 Jan
04:30PM
Venue Change
Dominik Rothenhaeusler ETH Zurich Anchor regression: Heterogeneous data meets causality
Thu 18 Jan
04:30PM
Extra Seminar
Anderson Zhang Yale University Mean field variational inference: Computational and statistical guarantees
Tue 16 Jan
12:15PM
Joint with MS&E
Guillaume Basse Harvard University Testing for two-stage experiments in the presence of interference
Thu 11 Jan
04:30PM
Day Change
Aaditya Ramdas UC Berkeley Interactive algorithms for multiple hypothesis testing
December 2017
Date/Time Speaker Affiliation Title
Tue 05 Dec
04:30PM
Weijie Su University of Pennsylvania HiGrad: Statistical inference for stochastic approximation and online learning
November 2017
Date/Time Speaker Affiliation Title
Tue 28 Nov
02:30PM
LKSC Berg A
A Memorial Symposium hosted by Stanford Statistics Remembering Charles Stein: Scientist, Colleague, and Friend
Tue 21 Nov
04:30PM
Thanksgiving Week --- No Seminar ---
Tue 14 Nov
04:30PM
Julia Palacios Stanford Statistics Different coalescent modeling resolutions for posterior inference of evolutionary parameters
Tue 07 Nov
04:30PM
Hidetoshi Shimodaira Kyoto University / RIKEN AIP Selective inference for the problem of regions via multiscale bootstrap
Thu 02 Nov
04:30PM
Extra Seminar
Galen Reeves Duke University Additivity of information in multilayer networks via additive Gaussian noise transforms
October 2017
Date/Time Speaker Affiliation Title
Tue 31 Oct
04:30PM
Zaid Harchaoui University of Washington Adaptive recovery of approximately shift-invariant signals by convex optimization
Tue 24 Oct
04:30PM
SBJC
Jasjeet Sekhon UC Berkeley Meta-learners for estimating heterogeneous treatment effects using machine learning
Tue 17 Oct
04:30PM
Alexander Volfovsky Duke University Design of experiments for networks with interference
Tue 10 Oct
04:30PM
Ryan Tibshirani Carnegie Mellon University Excess optimism: How biased is the apparent error of an estimator tuned by SURE?
Tue 03 Oct
04:30PM
Adrian Raftery University of Washington Probabilistic projection of carbon emissions
September 2017
Date/Time Speaker Affiliation Title
Tue 26 Sep
04:30PM
Zheng (Tracy) Ke University of Chicago Spectral approach to topic learning
Fri 22 Sep
03:30PM
Extra Seminar
Hau-tieng Wu Duke University Modern data science solutions to some medical time series challenges
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