« search calendars

« DIMACS Workshop on ADMM and Proximal Splitting Methods in Optimization

DIMACS Workshop on ADMM and Proximal Splitting Methods in Optimization

June 11, 2018 - June 13, 2018

Location:

DIMACS Center

Rutgers University

CoRE Building

96 Frelinghuysen Road

Piscataway, NJ 08854

Click here for map.

Organizer(s):

Farid Alizadeh, Rutgers University

Jonathan Eckstein, Rutgers University

Jean-Paul Watson, Sandia National Laboratory

David L. Woodruff, University of California - Davis

In the past decade, the alternating direction method of multipliers (ADMM) and related algorithms have gained significant popularity for convex optimization problems arising from areas such as: machine learning and analysis of “big data”; image processing; and stochastic optimization. ADMM-based approaches to stochastic programming have recently been applied in forestry and electric power systems, and the widely known progressive hedging algorithm for stochastic programming may, in fact, be viewed as a special case of ADMM.

The ADMM is part of a large family of algorithms that use proximal (implicit gradient or augmented Lagrangian) steps in conjunction with some kind of decomposition procedure, a class which we may generically call proximal operator splitting methods. They are relatively easy to implement, especially in parallel computing environments. Many new variants of these methods have recently arisen, as have a plethora of convergence rate analyses. The traditional analysis of these algorithms depends on problem monotonicity, a property that generalizes standard convexity assumptions for optimization problems. Nevertheless, applications to nonconvex and mixed-integer problems have started appearing, with various levels of success. Often these applications are strictly heuristic, but in some cases they have been shown to yield useful bounding and relaxation information.

This workshop will bring together theoreticians studying proximal operator splitting algorithms with practitioners using such methods for real-world optimization problems. A particular but not exclusive focus will be problems with nonconvex structures such as integrality constraints. Topics may include theoretical and empirical convergence rate studies, computational experiments on real large-scale problems, asynchronous parallel implementation, and analyzing the validity and accuracy of solutions obtained in nonconvex settings.  General goals of the workshop will be to make practitioners aware of the latest theoretical developments and algorithm variants, while exposing theoreticians to the most promising, interesting, timely, and challenging applications.

 

Monday, June 11, 2018

8:30 AM - 9:00 AM

Breakfast & Check in

9:00 AM - 9:10 AM

Welcome by Organizers

Jonathan Eckstein, Rutgers University

9:10 AM - 9:40 AM

The ADMM, Progressive Hedging, and Operator Splitting

Jonathan Eckstein, Rutgers University

9:40 AM - 10:10 AM

Proximal Envelopes

Panos Patrinos, Katholieke Universiteit Leuven

10:10 AM - 10:40 AM
10:40 AM - 11:10 AM

Break

11:10 AM - 11:40 AM

Decentralized Generation Scheduling in Energy Networks

Shabbir Ahmed, Georgia Institute of Technology

11:40 AM - 12:10 PM
12:10 PM - 1:40 PM

Lunch

1:40 PM - 2:10 PM

ADMM for Multiaffine Constrained Optimization

Don Goldfarb, Columbia University

2:10 PM - 2:40 PM

On Solving the Quadratic Shortest Path Problem

Renata Sotirov, Tilburg University

2:40 PM - 3:10 PM

Proximal Methods for Conic Optimization over Nonnegative Trigonometric Polynomials

Lieven Vandenberghe, University of California - Los Angeles

3:10 PM - 3:40 PM

Break

3:40 PM - 4:10 PM
4:10 PM - 4:40 PM
 

Tuesday, June 12, 2018

8:30 AM - 9:00 AM

Breakfast & Check in

9:00 AM - 9:10 AM

DIMACS Welcome

Tamra Carpenter, DIMACS

9:10 AM - 9:40 AM

ADMM, Accelerated-ADMM, and Continuous Dynamical Systems

Daniel Robinson, Johns Hopkins University

9:40 AM - 10:10 AM
10:10 AM - 10:40 AM
10:40 AM - 11:10 AM

Break

11:10 AM - 11:40 AM
11:40 AM - 12:10 PM
12:10 PM - 1:40 PM

Lunch

1:40 PM - 2:10 PM

On the Convergence and Complexity of Nonconvex ADMM

Shiqian Ma, University of California - Davis

2:10 PM - 2:40 PM
2:40 PM - 3:10 PM
3:10 PM - 3:40 PM

Break

3:40 PM - 4:10 PM
4:10 PM - 4:40 PM

Computational Experience with Asynchronous Projective Hedging

David L. Woodruff, University of California - Davis

5:45 PM - 7:30 PM

Workshop Dinner at Old Man Rafferty's

 

Wednesday, June 13, 2018

8:30 AM - 9:00 AM

Breakfast & Check-in

9:00 AM - 9:30 AM
9:30 AM - 10:00 AM
10:00 AM - 10:30 AM

Solving ADMM Subproblems using Relative Error Criteria

Jefferson Melo, Federal University of Goiás

10:30 AM - 11:00 AM

Break

11:00 AM - 11:30 AM

Douglas-Rachford Splitting for Pathological Problems

Wotao Yin, University of California - Los Angeles

11:30 AM - 12:00 PM
12:00 PM - 1:30 PM

Lunch

1:30 PM - 2:00 PM
2:00 PM - 2:30 PM
2:30 PM - 3:00 PM
 

Presentations are by invitation. Attendance at the workshop is open to all interested participants (subject to space limitations). Please register if you would like to attend this workshop.

Open to Registered Participants

Registration for this event is closed.