[Colloquium] 2/24: Data Science/Stats Candidate Talk - Madeleine Udell (Cornell)

[Rob Mitchum]

*Data Science Institute/Statistics Candidate Seminar*

*Madeleine Udell*
*Assistant Professor*
*Cornell University*

*Thursday, February 24th*
*4:30 p.m. - 5:30 p.m.*
*REMOTE ONLY: Live Stream
<http://live.cs.uchicago.edu/madeleineudell/> or Zoom
<https://uchicago.zoom.us/j/96845604580?pwd=T3BkdHYzaE1ja2hzSDc1VzdHbTFEZz09>
(details
below)*


*Low Rank Approximation for Faster Convex Optimization*

Low rank structure is pervasive in real-world datasets. This talk shows how
to accelerate the
solution of fundamental computational problems, including eigenvalue
decomposition, linear system solves, and composite convex optimization, by
exploiting this low rank structure. We present a simple and efficient
method for approximate top eigendecomposition based on randomized numerical
linear algebra. Armed with this primitive, we design a new randomized
preconditioner for the conjugate gradient method, and a method called
NysADMM, based on the inexact alternating directions method of multipliers,
for composite convex optimization. These methods come with strong
theoretical and numerical support. Indeed, a simple implementation of
NysADMM solves important large-scale statistical problems like lasso,
logistic regression, and support vector machines 2--58x faster than
standard solvers.

*Bio*: Madeleine Udell <https://people.orie.cornell.edu/mru8/> is Assistant
Professor of Operations Research and Information Engineering and Richard
and Sybil Smith Sesquicentennial Fellow at Cornell University. She studies
optimization and machine learning for large scale data analysis and
control, with applications in marketing, demographic modeling, medical
informatics, engineering system design, and automated machine learning. She
has received several awards, including an Alfred P. Sloan Research
Fellowship (2021), a National Science Foundation CAREER award (2020), an
Office of Naval Research (ONR) Young Investigator Award (2020), a Cornell
Engineering Research Excellence Award (2020), an INFORMS Optimization
Society Best Student Paper Award (as advisor) (2019), and INFORMS Doing
Good with Good OR (2018). Her work is supported by grants from the NSF,
ONR, DARPA, the Canadian Institutes of Health, and Capital One.

*Host*: Rebecca Willett

*Zoom Info:*
Zoom:
https://uchicago.zoom.us/j/96845604580?pwd=T3BkdHYzaE1ja2hzSDc1VzdHbTFEZz09
ID: 968 4560 4580
Password: ds2022



-- 
*Rob Mitchum*

*Associate Director of Communications for Data Science and Computing*
*University of Chicago*
*rmitchum at uchicago.edu <rmitchum at ci.uchicago.edu>*
*773-484-9890*
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