Optimization, Statistics and Uncertainty
Organizers:
This workshop aims to explore the emerging connections between optimization, statistics and machine learning. It will discuss ties, both well-known and anticipated, between optimization and various approaches to modeling, reasoning about and coping with uncertainty. Some of the key topics that will be covered are: unsupervised machine learning, computational hardness in statistics, differential privacy and its applications in statistics and machine learning, online regret minimization, robust optimization and planted models.
Emmanuel Abbe (Princeton University), Nima Anari Ahmadipouranari (Stanford University), Farid Alizadeh (Rutgers University), Zeyuan Allen-Zhu (Microsoft Research), Kyriakos Axiotis (MIT), Misha Belkin (Ohio State University), Quentin Berthet (University of Cambridge), Sébastien Bubeck (Microsoft Research), Deeparnab Chakrabarty (Dartmouth College), Yuxin Chen (Princeton University), Ken Clarkson (IBM Almaden), Michael Cohen (MIT), Alex d'Aspremont (École Normale Supérieure), Jelena Diakonikolas (Boston University), Reza Eghbali (University of Washington), Friedrich Eisenbrand (École Polytechnique Fédérale de Lausanne), Maryam Fazel (University of Washington), Sam Fiorini (Universite libre de Bruxelles), Avishek Ghosh (Ohio State University), Ben Grimmer (Cornell University), Anupam Gupta (Carnegie Mellon University), Swati Gupta (MIT), Moritz Hardt (UC Berkeley), Rebecca Hoberg (University of Washington), Ravi Kannan (Microsoft Research India), Samir Khuller (University of Maryland), Alexandra Kolla (University of Illinois at Urbana-Champaign), Matthias Köppe (UC Davis), Robi Krauthgamer (Weizmann Institute of Science), Fatma Kılınç-Karzan (Carnegie Mellon University), Bundit Laekhanukit (Weizmann Institute of Science), Yin-Tat Lee (University of Washington), Euiwoong Lee (Carnegie Mellon University), James Lee (University of Washington), Katrina Ligett (Hebrew University of Jerusalem), Cong Han Lim (University of Wisconsin-Madison), Mike Luby (Qualcomm), Tengyu Ma (Princeton University), Shiqian Ma (UC Davis), Aleksander Madry (MIT), Aryan Mokhtari (University of Pennsylvania), Andrea Montanari (Stanford University), Sarah Maria Morell (EPFL), Walaa Moursi (University of British Columbia), Seffi Naor (Technion Israel Institute of Technology), Sahand Negahban (Yale University), Neil Olver (Vrije Universiteit), Lorenzo Orecchia (Boston University), Pablo Parrilo (MIT), Kostya Pashkovich (University of Waterloo), Prasad Raghavendra (UC Berkeley), Max Raginsky (University of Illinois at Urbana-Champaign), Sasha Rakhlin (University of Pennsylvania), Daniel Ramos Vaz (Max Planck Institut für Informatik), Ben Recht (UC Berkeley), Philippe Rigollet (MIT), Aviad Rubinstein (UC Berkeley), Ludwig Schmidt (MIT), Sahil Singla (Carnegie Mellon University), Thomas Steinke (IBM Almaden), Ola Svensson (EPFL), Jakub Tarnawski (EPFL), Kim-Chuan Toh (National University of Singapore), Dimitris Tsipras (MIT), Levent Tunçel (University of Waterloo), Jonathan Ullman (Northeastern University), Santosh Vempala (Georgia Institute of Technology), Soledad Villar (University of Texas at Austin), Adrian Vladu (Boston University), Di Wang (UC Berkeley), Rachel Ward (University of Texas at Austin), Steve Wright (University of Wisconsin-Madison), Yinyu Ye (Stanford University), Chenyang Yuan (MIT)
