Operator Splitting Methods in Data Analysis

Organized by

Patrick L. Combettes                                 Christian L. Müller
Distinguished Professor,                              Project Leader in Computational
Mathematics, North Carolina                      Statistics, Numerical Analysis,
State University                                           CCM, Flatiron Institute

The 2nd workshop on Operator Splitting Methods in Data Analysis brings together experts from nonlinear analysis, optimization, data analysis, and statistics to advance the field of operator splitting methods and its application to statistics and data analysis.

Specific topics include:
(i) general forms of equilibria that are captured by monotone inclusions,
(ii) nonconvex/nonmonotone splitting methods
(iii) scaling up of splitting strategies as the numbers of observations and features grow
(iv) robustness of splitting methods under perturbations and modeling errors
(v) New and nonstandard variational formulations for data analysis problems
(vi) Applications of splitting methods in data analysis and statistics

A unique aspect will be again the strong focus on presentations that illuminate technical difficulties and highlight open problems.

Information about the 2018 edition of this workshop, held at SAMSI, can be found here (https://www.samsi.info/programs-and-activities/research-workshops/operator-splitting-methods-data-analysis/).