Bridging Mathematical Optimization, Information Theory, and Data Science

Recent years have witnessed a flurry of exciting new developments and activities in the intersection of optimization theory, information theory, and mathematical data science. For instance, optimization theory inspires algorithmic breakthroughs in machine learning and reinforcement learning; information theory offers powerful tools for understanding the fundamental limits in numerous data science applications; and the growing popularity of data science and statistical learning in turn provides new data-driven perspectives to optimization paradigms and enriches the toolbox of information theory.  The goal of this workshop is to bring together participants from multiple communities including mathematical optimization, information theory, statistics, and machine learning in order to conduct in-depth discussion and foster interdisciplinary collaboration.



    Workshop Information

    05/14/2018 - 05/16/2018
    Princeton Center for Theoretical Science (PCTS)
    Room 407, Jadwin Hall

    The Workshop Schedule is available here


    For Registration and travel information, please visit the PCTS website here:

    Confirmed Speakers:
    • Peter Bartlett (UC Berkeley)
    • Sebastien Bubeck (Microsoft Research)
    • Yuejie Chi (Carnegie Melon University)
    • Alex Dimakis (University of Texas at Austin)
    • Donald Goldfarb (Columbia University)
    • Alfred Hero (University of Michigan)
    • Guanghui Lan (Georgia Tech)
    • Zongming Ma (University of Pennsylvania)
    • Ankur Moitra (MIT)
    • Andrea Montanari (Stanford University)
    • Arkadi Nemirovski (Georgia Tech)
    • Robert Nowak (University of Wisconsin)
    • Sewoong Oh (UIUC)
    • Raghu Pasupathy (Purdue University)
    • Alex Shapiro (Georgia Tech)
    • David Tse (Stanford University)
    • Pramod Viswanath (UIUC)
    • Rachel Ward (University of Texas at Austin)
    • John Wright (Columbia University)
    • Stephen Wright (University of Wisconsin)
    • Yihong Wu (Yale University)
    • Wotao Yin (University of California, Los Angeles)
    • Ming Yuan (Columbia University)
    • Anru Zhang (University of Wisconsin)
    • Harrison Zhou (Yale University)

    Princeton Center for Theoretical Science (PCTS) CSML Electrical Engineering    ORFE