The DIMACS/Simons Collaboration on Bridging Continuous and Discrete Optimization is a research coordination network (RCN) led by DIMACS and the Simons Institute for the Theory of Computing to conduct activities devoted to advancing capabilities in optimization by promoting collaborations that bridge continuous and discrete optimization. The Collaboration features activities at both DIMACS and the Simons Institute, bringing together computer scientists, mathematicians, operations researchers, engineers, statisticians, and algorithm developers to advance both the foundations and applications of optimization.
Optimization tools and algorithms have transformed fields ranging from biology to finance, and they touch everyday lives through more efficient supply chains, better traffic management, and more secure power grids. New applications, particularly those stemming from machine learning and data science, are now challenging the field to solve larger and more complex problems on smaller devices in less time. The field is responding with innovative approaches leading to advances such as faster algorithms for maximum flow and near-real-time approximations, more efficient interior-point methods, and faster cutting-plane methods. Many of these breakthroughs bring together ideas from both continuous and discrete optimization. The DIMACS/Simons Collaboration on Bridging Continuous and Discrete Optimization aims to accelerate progress by stimulating collaboration across the many communities of optimization.
The Collaboration kicks off with an intensive program on Bridging Continuous and Discrete Optimization at the Simons Institute during the fall of 2017. This program is a “jumbo program” that is about twice the size of a typical program at the Simons Institute. The Simons program is immediately followed by the DIMACS Special Focus on Bridging Continuous and Discrete Optimization, beginning in January 2018 and continuing for multiple years.
Beginning with a Boot Camp to introduce key themes, the Simons program brings together roughly 120 long-term participants (including students) in residence at the Simons Institute. The Simons program also includes workshops on:
- Discrete Optimization via Continuous Relaxation;
- Fast Iterative Methods in Optimization;
- Hierarchies, Extended Formulations and Matrix-Analytic Techniques; and
- Optimization, Statistics and Uncertainty.
The DIMACS program builds on the intensive activity of the Simons program to engage additional people, bringing researchers working in the theoretical computer science and algorithmic aspects of optimization together with others including mathematicians, operations researchers and industrial engineers working on large-scale mathematical programming approaches, machine learning researchers, and statisticians to advance both the practical performance of optimization methods and the foundational principles upon which they are built. It aims to advance the state of the art and of the practice of the foundations and applications of optimization via research visits, collaboration with additional activities and institutes, and seven additional workshops on the topics of:
- Optimization and Machine Learning;
- ADMM and Proximal Splitting Methods in Optimization;
- Randomized Numerical Linear Algebra, Statistics, and Optimization;
- Entropy & Optimization;
- Polynomial Optimization;
- Optimization in Distance Geometry; and
- Mixed-Integer Nonlinear Programming.
As the special focus progresses, new events and activities that align with the theme may be added. For the the most up-to-date list of special focus activities, please see the calendar for the Special Focus on Bridging Continuous and Discrete Optimization.
An overarching goal of the RCN is to help facilitate broad collaborations. To help achieve this goal, the RCN is partnering with additional projects and institutes in coordinating and co-sponsoring activities. The workshop on Mixed Integer Nonlinear Optimization will be held at Polytechnique Montréal in collaboration with a month-long program on Mixed Integer Nonlinear Programming sponsored by the Centre de Recherches Mathématiques (CRM). The workshop on Optimization and Machine Learning is being planned in collaboration with the TRIPODS Institute for Optimization and Learning at Lehigh University. Other workshops will coordinate with and relate to future programs at the Simons Institute on Foundations of Data Science and Geometry of Polynomials.
The DIMACS/Simons Collaboration on Bridging Continuous and Discrete Optimization is led by a Steering Committee of:
- Farid Alizadeh, Rutgers University
- Tamra Carpenter, Rutgers University
- Shafi Goldwasser, UC Berkeley
- Stefanie Jegelka, Massachusetts Institute of Technology
- Jon Lee, University of Michigan
- Leo Liberti, CNRS
- Aleksander Mądry, Massachusetts Institute of Technology
- Pablo Parrilo, Massachusetts Institute of Technology
- Katya Scheinberg, Cornell University
- Nisheeth Vishnoi, Yale University
- Tamra Carpenter, Rutgers University
The DIMACS/Simons Collaboration on Bridging Continuous and Discrete Optimization is supported by the National Science Foundation under grant number CCF-1740425.