Workshop on ADMM and Proximal Splitting Methods in Optimization

Slides from Presentations (alphabetical by speaker)

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Shabbir Ahmed, Georgia Institute of Technology
Decentralized Generation Scheduling in Energy Networks

Maicon Alves, Federal University of Santa Catarina
A Parallel Forward-backward Splitting Method for Multiterm Composite Convex Optimization

Hedy Attouch, University of Montpellier
Relaxed Inertial Proximal Algorithms for Monotone Inclusions

Serhat Aybat, Pennsylvania State University
An Accelerated Primal-dual Algorithm for General Convex-Concave Saddle Point Problems

Radu Bot, University of Vienna
The Proximal Alternating Direction Method of Multipliers in the Nonconvex Setting: Convergence Analysis and Rates

Yu Du, University of Colorado - Denver
Selective Linearization for Multi-block Statistical Learning Problems

Jonathan Eckstein, Rutgers University
The ADMM, Progressive Hedging, and Operator Splitting

Pontus Giselsson, Lund University
On Linear Convergence for Douglas-Rachford splitting and ADMM

Don Goldfarb, Columbia University
ADMM for Multiaffine Constrained Optimization

Patrick Johnstone, Rutgers University
Projective Splitting with Forward Steps: Asynchronous and Block-Iterative Operator Splitting

Jim Luedtke, University of Wisconsin
Combining Progressive Hedging with a Frank-Wolfe Method to Compute Lagrangian Dual Bounds in Stochastic Mixed-Integer Programming

Shiqian Ma, University of California - Davis
On the Convergence and Complexity of Nonconvex ADMM

Peter Melchior, Princeton University
Source Separation in Astronomy with Constrained Matrix Factorization

Walaa Moursi, Stanford University
On the Order of the Operators in the Douglas-Rachford Algorithm

Panos Patrinos, Katholieke Universiteit Leuven
Proximal Envelopes

Daniel Robinson, Johns Hopkins University
ADMM, Accelerated-ADMM, and Continuous Dynamical Systems

Terry Rockafellar, University of Washington
Augmented Lagrangians and Decomposition in Convex and Nonconvex Programming

Ernest Ryu, UCLA
Uniqueness of DRS as the 2 Operator Resolvent-Splitting and Impossibility of 3 Operator Resolvent-Splitting

Defeng Sun, Hong Kong Polytechnic University
On the Equivalence of Inexact Proximal ALM and ADMM for a Class of Convex Composite Programming

Kim-Chuan Toh, National University of Singapore
A Block Symmetric Gauss-Seidel Decomposition Theorem for Convex Composite QP and its Applications to Multi-block ADMM

Lieven Vandenberghe, University of California - Los Angeles
Proximal Methods for Conic Optimization over Nonnegative Trigonometric Polynomials

David L. Woodruff, University of California - Davis
Computational Experience with Asynchronous Projective Hedging

Wotao Yin, University of California - Los Angeles
Douglas-Rachford Splitting for Pathological Problems