[Iefac.list] Lehigh ISE Spencer C. Schantz Distinguished Lecture: Stephen J. Wright

Fri Jul 1 13:24:15 EDT 2022

Lehigh ISE is pleased to announce Stephen J. Wright will give the next
Spencer C. Schantz Distinguished Lecture
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Dear Lehigh ISE Community,

The Lehigh ISE Department
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is pleased to announce that Professor Stephen J. Wright
<https://r20.rs6.net/tn.jsp?f=001FlOlEj7eiPY1W6l3GTEg8hkdmpUS30hBd1y_YDMKBoxZTJtc_xqi8YTFd6sKz9V5wv5Kd2kpa-7TT6zHGRxRahzRFyi90uiCPFbAs7MNIePwqXQ75DBrt3--QFb3LdUYq8rc5JZ78MICR2A28wbLkpG7pnucH49T&c=gopK2zPn6-HYy67TUBNXpIxAuZsLk_ve7TFCpBYwYwSKsKEG7P957Q==&ch=IlL3Pg3Uh0rKqH3CMTm5-zOtr-83Mv8G0KTZUta5yE3oEv6X82g7Gw==>,
the George B. Dantzig, the Sheldon Lubar, and the Amar and Balinder Sohi
Professor of Computer Sciences at the University of Wisconsin-Madison, will
give the Spencer C. Schantz Distinguished Lecture (technical talk)
titled Primal-Dual
Optimization Methods for Robust Machine Learning and Generalized Linear
Programming on Thursday, July 28, 2022, from 5:00 p.m. to 6:00 p.m., via
Zoom.

The Zoom link is https://lehigh.zoom.us/j/97904256912
<https://r20.rs6.net/tn.jsp?f=001FlOlEj7eiPY1W6l3GTEg8hkdmpUS30hBd1y_YDMKBoxZTJtc_xqi8YTFd6sKz9V59XK9-oyxI4TCg4lMeDmKHEV07ApoC3Vo0ftUSLx2Nv1c9Am4iPlZv9LKBcZkcZxm1ZCLo2lTAU_zcuulOyAexc-UUJUeaGAf&c=gopK2zPn6-HYy67TUBNXpIxAuZsLk_ve7TFCpBYwYwSKsKEG7P957Q==&ch=IlL3Pg3Uh0rKqH3CMTm5-zOtr-83Mv8G0KTZUta5yE3oEv6X82g7Gw==>.
Meeting ID: 979 0425 6912.

Lehigh faculty and students and ICCOPT 2022 participants will be able to
see and listen to the lecture in Perella Auditorium (Room 184), Rauch
Business Center.

All questions must be posted in the Zoom chat (even for local
participants).

Abstract: We consider a convex-concave primal-dual optimization framework
in which the coupling between primal and dual variables is bilinear. This
framework admits linearly constrained optimization together with a variety
of interesting problems in machine learning, including (linear) empirical
risk minimization with various regularization terms. It also includes a
formulation that we term “generalized linear programming'” (GLP) in which
regularization terms and constraints are added to the traditional linear
programming formulation, provided they admit efficient prox operations.
Problems from differentially robust optimization (DRO), using either
f-divergence metrics or Wasserstein metrics, can be formulated as GLPs.

We describe algorithms for our framework that take prox-gradient steps
alternately in the primal and dual variables, but incorporate such
additional features as coordinate descent, variance reduction, dual
averaging, importance sampling, and iterate averaging. Our methods can also
exploit sparsity in the matrix that couples primal and dual variables. Our
methods match or improve on the best-known worst-case complexity bounds in
various settings. Computational experiments indicate that our methods also
have good practical performance.

The talk represents joint work with Ahmet Alacaoglu, Jelena Diakonikolas,
Chaobing Song, Eric Lin, and Volkan Cevher.

Bio: Stephen J. Wright holds the George B. Dantzig Professorship, the
Sheldon Lubar Chair, and the Amar and Balinder Sohi Professorship of
Computer Sciences at the University of Wisconsin-Madison. His research is
in computational optimization and its applications to data science and many
other areas of science and engineering. Prior to joining UW-Madison in
2001, Wright held positions at North Carolina State University (1986-1990)
and Argonne National Laboratory (1990-2001). He has served as Chair of the
Mathematical Optimization Society (2007-2010) and as a Trustee of SIAM for
the maximum three terms (2005-2014). He is a Fellow of SIAM. In 2014, he
won the W.R.G. Baker Award from IEEE for best paper in an IEEE archival
publication during 2009-2011. He was awarded the Khachiyan Prize by the
INFORMS Optimization Society in 2020 for lifetime achievements in
optimization and received the NeurIPS Test of Time Award in 2020 for a
paper presented at that conference in 2011. Prof. Wright is the author /
coauthor of widely used text and reference books in optimization including
“Primal Dual Interior-Point Methods” and “Numerical Optimization” and, most
recently, “Optimization for Data Analysis.” He has published widely on
optimization theory, algorithms, software, and applications. Prof. Wright
served from 2014-2019 as Editor-in-Chief of the SIAM Journal on
Optimization and previously served as Editor-in-Chief of Mathematical
Programming Series B. He has also served as Associate Editor of
Mathematical Programming Series A, SIAM Review, SIAM Journal on Scientific
Computing, and several other journals and book series.

Spencer C. Schantz Distinguished Lecture Series: This lecture series is
endowed in the name of the late Spencer C. Schantz, who graduated from
Lehigh in 1955 with a B.S. in Industrial Engineering. Following progressive
responsibilities with several electrical manufacturing companies, in 1969
he founded U.S. Controls Corporation and became its first CEO and
President. The Spencer C. Schantz Distinguished Lecture Series
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was established by his wife Jerelyn as a valuable educational experience
for faculty, students, and friends of Lehigh’s Industrial and Systems
Engineering department.

Sincerely,
‌
Luis Nunes Vicente
Timothy J. Wilmott Endowed Chair Professor and Department Chair
Department of Industrial and Systems Engineering, Lehigh University

Industrial and Systems Engineering
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