About
The focus of this workshop will be on recent developments in randomized linear algebra, with an emphasis on how algorithmic improvements from the theory of algorithms interact with statistical, optimization, inference, and related perspectives. One focus area of the workshop will be the broad use of sketching techniques developed in the data stream literature for solving optimization problems in linear and multi-linear algebra. The workshop will also consider the impact of theoretical developments in randomized linear algebra on (i) numerical analysis as a method for constructing preconditioners; (ii) applications as a principled feature selection method; and (iii) implementations as a way to avoid communication rather than computation. Another goal of this workshop is thus to bridge the theory-practice gap by trying to understand the needs of practitioners when working on real datasets.
Chairs/Organizers
Invited Participants
Ery Arias-Castro (UC San Diego), Haim Avron (Tel Aviv University), Laura Balzano (University of Michigan), Peter Bartlett (UC Berkeley), Soheil Behnezhad (University of Maryland), Shai Ben-David (University of Waterloo), Kush Bhatia (UC Berkeley), Vladimir Braverman (Johns Hopkins University), Yeshwanth Cherapanamjeri (UC Berkeley), Artur Czumaj (University of Warwick), Jelena Diakonikolas (Boston University), Charlie Dickens (University of Warwick), Mark Embree (Virginia Tech), Matan Gavish (Hebrew University of Jerusalem), Amir Gholaminejad (UC Berkeley), Alex Gittens (Rensselaer Polytechnic Institute), David Gleich (Purdue University), Wooseok Ha (UC Berkeley), Ilse Ipsen (North Carolina State University), Chi Jin (UC Berkeley), John Kallaugher (University of Texas at Austin), Ravi Kannan (Microsoft Research India), Yiannis Koutis (New Jersey Institute of Technology), Rasmus Kyng (Harvard University), Francois Lanusse (UC Berkeley), Jerry Li (Massachusetts Institute of Technology), Lek-heng Lim (University of Chicago), Ping Ma (University of Georgia), Per-Gunnar Martinsson (University of Texas at Austin), Shannon McCurdy (UC Berkeley), Dustin Mixon (Ohio State University), Marco Mondelli (Stanford University), Cameron Musco (Microsoft Research New England), Christopher Musco (MIT), Deanna Needell (University of California, Los Angeles), Praneeth Netrapalli (Microsoft Research India), Huy Nguyen (Northeastern University), Rasmus Pagh (IT University of Copenhagen), Sourabh Palande (University of Utah), Richard Peng (Georgia Institute of Technology), Jeff Phillips (University of Utah), Eric Price (University of Texas at Austin), Peter Richtarik (University of Edinburgh), Fred Roosta (University of Queensland), Barna Saha (University of Massachusetts Amherst), Sujay Sanghavi (University of Texas at Austin), Michael Saunders (Stanford University), Uros Seljak (UC Berkeley), Nikhil Srivastava (UC Berkeley), Yan Shuo Tan (University of Michigan), Madeleine Udell (Cornell University), Anastasia Voloshinov (USC), Ruosong Wang (Carnegie Mellon University), David Woodruff (Carnegie Mellon University)