Conference Program Home
  My Program

All Times EDT

Abstract Details

Activity Number: 97 - New Methods for Structured Variable Selection
Type: Topic Contributed
Date/Time: Monday, August 8, 2022 : 8:30 AM to 10:20 AM
Sponsor: SSC (Statistical Society of Canada)
Abstract #322198
Title: Flexible Regularized Estimating Equations: Some New Perspectives
Author(s): Yi Yang*
Companies: McGill University
Keywords: regularization; estimating equations; fixed-point problems; variational inequalities

We make some observations about the equivalences between regularized estimating equations, fixed-point problems and variational inequalities: (a) A regularized estimating equation is equivalent to a fixed-point problem, specified via the proximal operator of the corresponding penalty. (b) A regularized estimating equation is equivalent to a (generalized) variational inequality. Both equivalences extend to any estimating equations with convex penalty functions. To solve large-scale regularized estimating equations, it is worth pursuing computation by exploiting these connections. While fast computational algorithms are less developed for regularized estimating equation, there are many efficient solvers for fixed-point problems and variational inequalities. In this regard, we apply some efficient and scalable solvers which deliver hundred-fold speed improvement. These connections can lead to further research in both computational and theoretical aspects of the regularized estimating equations.

Authors who are presenting talks have a * after their name.

Back to the full JSM 2022 program