[Sds-seminars] S&DS In-Person Seminar, Rina Foygel Barber, 12/05 @ 4pm-5pm, "Testing the stability of a black-box algorithm"

[elizavette.torres at yale.edu]

 <https://statistics.yale.edu/>     <https://statistics.yale.edu/>
Department of Statistics and Data Science

In-Person seminars will be held at Dunham Lab, 10 Hillhouse Ave., Room 220,
with an option of remote participation via zoom.

 <x-apple-data-detectors://10/> 3:30pm -   Pre-talk meet and greet, DL Suite
222, Room 228



 <https://statistics.yale.edu/seminars/rina-foygel-barber-0> Rina Foygel
Barber, University of Chicago



Date: Monday, December 05, 2022

Time: 4:00PM to 5:00PM

Location: Dunbar Lab.  <http://maps.google.com/?q=10+Hillhouse+Avenue%2C+Rm.
+220%2C+New+Haven%2C+CT%2C+06511%2C+us> see map

10 Hillhouse Avenue, Rm. 220

New Haven, CT 06511

https://statistics.yale.edu/seminars/rina-foygel-barber-0



Zoom Option:
https://yale.zoom.us/j/92411077917?pwd=aXhnTnFGRXFoaTVDczNjeFFKeWpTQT09  /
Password: 24



Title: Testing the stability of a black-box algorithm



Information and Abstract:

Many results on generalization and distribution-free inference depend on the
stability of a regression algorithm, which is often defined as the property
that predictions on a new test point are not substantially altered by
removing a single point at random from the training set. However, this
stability property itself is an assumption that may not hold for highly
complex predictive algorithms and/or nonsmooth data distributions. In this
work we ask whether it is possible to infer the stability of an algorithm
through “black-box testing”, where we cannot study the algorithm
theoretically but instead try to determine its stability properties by the
behavior of the algorithm on various data sets. Our results establish
fundamental limits on the stability testing problem in the distribution-free
setting.

This work is joint with Byol Kim.

In-Person seminars will be held at Dunham Lab, 10 Hillhouse Ave., Room 220,
with an option of remote participation via zoom.

Link: Join from PC, Mac, Linux, iOS or Android:
https://yale.zoom.us/j/92411077917?pwd=aXhnTnFGRXFoaTVDczNjeFFKeWpTQT09

Password: 24

Or Telephone：203-432-9666 (2-ZOOM if on-campus) or 646 568 7788

Meeting ID: 924 1107 7917










Department of Statistics and Data Science


Yale University
24 Hillhouse Avenue
New Haven, CT 06511

t 203.432.0666
f 203.432.0633



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