[Colloquium] TODAY, 4:30: Data Science/Stats Candidate Talk - Yu-Xiang Wang (UCSB)

[Rob Mitchum]

*Data Science Institute/Statistics Candidate Seminar*


*Yu-Xiang Wang*
*Assistant Professor*
*University of California, Santa Barbara*

*Monday, March 7th*
*4:30 p.m. - 5:30 p.m.*
*In Person: John Crerar Library, Room 390*
*Remote: Live Stream <http://live.cs.uchicago.edu/yuxiangwang/> or Zoom
<https://uchicago.zoom.us/j/91890556990?pwd=cXArN1NqTGJaK0hIeS8yMzVtcWRMQT09>
(details
below)*

The rise of machine learning (ML) and deep learning has revolutionized
almost every aspect of our daily life. Learning-based methods are now
widely used in financial, medical, and legal applications for tasks
involving not only predictions, but also decision making, often in
adversarial, non-stationary, and strategic environments, and sometimes
relying on sensitive data. Classical statistical learning theory does not
cover these new settings, which motivates us to develop new theories and
algorithms for applying ML responsibly in these emerging applications.

In this talk, I will cover recent advances that address these challenges
with strong theoretical guarantees. Topics include new technical results in
offline reinforcement learning, adaptive online learning and differential
privacy as well as their promise in real-life applications.

*Bio*: Yu-Xiang Wang <https://sites.cs.ucsb.edu/~yuxiangw/> is the Eugene
Aas Assistant Professor of Computer Science at UCSB. He runs the
Statistical Machine Learning lab and co-founded the UCSB Center for
Responsible Machine Learning. Prior to joining UCSB, he was a scientist
with Amazon Web Services’s AI research lab in Palo Alto, CA. Yu-Xiang
received his PhD in Statistics and Machine Learning in 2017 from Carnegie
Mellon University (CMU). Yu-Xiang’s research interests include statistical
theory and methodology, differential privacy, reinforcement learning,
online learning and deep learning. His work had been supported by an NSF
CAREER Award, Amazon ML Research Award, Google Research Scholar Award,
Adobe Data Science Research Award and had received paper awards from
KDD’15, WSDM’16, AISTATS’19 and COLT’21.

*Host*: Chao Gao

*Zoom Info:*
https://uchicago.zoom.us/j/91890556990?pwd=cXArN1NqTGJaK0hIeS8yMzVtcWRMQT09
ID: 918 9055 6990
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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