The Conference on Nonconvex Statistical Learning was held at the University of Southern California May 26-27, 2017. The goal of the conference was to pull together “researchers at all levels, from established to junior, and from cross disciplines that include computational and applied mathematics, optimization, statistics, computer science, and engineering to report on the state of the art of the conference subject, to exchange ideas for its further development, and to foster collaborations among the participants with the goal of advancing the science of the field of tistical learning and promoting the interfaces of the involved disciplines.”
The workshop was sponsored by the Division of Mathematical Sciences at the National Science Foundation; the Epstein Institute; and the Daniel J. Epstein Department of Industrial and Systems Engineering, University of Southern California.
Jong-Shi Pang, University of Southern California
Yufeng Liu, University of North Carolina at Chapel Hill
Jack Xin, University of California at Irvine
Meisam Razaviyayn, University of Southern California
Phebe Vayanos, University of Southern California
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