Workshop on Recent Advances in Optimization

December 6 - 7, 2022, The Fields Institute

Location: Fields Institute, Stewart Library

Description

This workshop explores recent theoretical as well as practical progress made in the area of optimization. The goal is to develop connections among practitioners in academia and industry and raise awareness of the most recent advances in optimization theory, algorithms and applications. This workshop aims to take a significant step towards building a bridge for researchers, practitioners, and students from diverse backgrounds to allow focused discussions on current practical challenges and to promote future collaborations.

For remote participants: https://zoom.us/j/93153973083

Schedule

Tuesday, December 6th, 2022
09:30 to 10:00	Coffee Break
10:00 to 10:30	Revisiting von Neumann’s alternating projections Sebastian Pokutta, Technical University of Berlin and ZIB
10:30 to 11:00	Stochastic Multi-level Nested Composition Optimization Saeed Ghadimi, University of Waterloo
11:00 to 11:30	Neur2SP: Neural Two-Stage Stochastic Programming Elias Khalil, University of Toronto
11:30 to 12:00	Integer programming methods for causal structure learning Sanjeeb Dash, IBM Research
12:00 to 13:00	Lunch
13:30 to 13:50	Screening for Sparse Logistics Regression Anna Deza, University of California Berkeley
13:50 to 14:10	The warehouse problem with fixed costs and complementarity constraints Ishan Bansal, Cornell University
14:10 to 14:30	Leveraging Combinatorial Symmetries in Flag Algebra-based SDP Formulations Christoph Spiegel, Zuse Institute Berlin (ZIB) / TU Berlin
14:30 to 15:00	Coffee Break
15:00 to 15:30	Maximum-entropy sampling: Algorithms and Application Jon Lee, University of Michigan
15:30 to 16:00	Random Projections for Quadratically Constrained Quadratic Programs Leo Liberti, Centre national de la recherche scientifique (CNRS) and Ecole Polytechnique
16:00 to 16:30	Sparse Training with Lipschitz Continuous Loss Functions and a Weighted Group L0-norm Constraint Michael Metel, Huawei Canada

Wednesday, December 7th, 2022
09:30 to 10:00	Coffee Break
10:00 to 10:30	2x2-convexifications for convex quadratic optimization with indicator variables Alper Atamtürk, University of California Berkeley
10:30 to 11:00	Two-stage and Lagrangian Dual Decision Rules for Multistage Adaptive Robust Optimization Merve Bodur, University of Toronto
11:00 to 11:30	P-split formulations: a class of adjustable formulations between big-M and convex hull for disjunctive constraints Jan Kronqvist, KTH - Kungliga Tekniska högskolan
11:30 to 12:00	Some Machine Learning Techniques in OptVerse Solver Zirui Zhou, Huawei Technologies Canada
12:00 to 13:00	Lunch
13:30 to 13:50	Facial Reduction for the SDP Relaxation of the Maximum $k$-Cluster Problem Ian Sugrue, Northern Illinois University
13:50 to 14:10	On the singularity degree of non facially exposed faces Fei Wang, University of Waterloo
14:10 to 14:30	Leveraging Decision Diagrams to Solve Two-stage Stochastic Programs with Binary Recourse and Logical Linking Constraints Moira MacNeil, University of Toronto
14:30 to 15:00	Coffee Break
15:00 to 15:30	Incorporating Dantzig-Wolfe Decomposition Into Branch-and-Cut by Cutting Planes Oktay Günlük, Cornell University
15:30 to 16:00	Can an infeasible MIP solve itself? Yuriy Zinchenko, Gurobi Inc. and University of Calgary
16:00 to 16:30	Solving the Nearest Correlation Matrix Problem with an Inexact Accelerated Proximal Gradient Method Nathan Krislock, Northern Illinois University

Registered Participants

Name	Affiliation
Alper Atamtürk	University of California Berkeley
Ishan Bansal	Cornell University
Merve Bodur	University of Toronto
Sanjeeb Dash	IBM Research
Anna Deza	University of California Berkeley
Antoine Deza	McMaster University
Arnaud Deza	University of Toronto
Justin Dumouchelle	University of Toronto
Zhenan Fan	Huawei Technologies Canada
Bissan Ghaddar	Western University
Saeed Ghadimi	University of Waterloo
Oscar Guaje	University of Toronto
Oktay Günlük	Cornell University
Hanheng He	McMaster University
Weimin Huang	University of Toronto
Haesol Im	University of Waterloo
Elias Khalil	University of Toronto
Nathan Krislock	Northern Illinois University
Jan Kronqvist	KTH - Kungliga Tekniska högskolan
Connor Lawless	Cornell University
Jon Lee	University of Michigan
Leo Liberti	Centre national de la recherche scientifique (CNRS) and Ecole Polytechnique
Bo Lin	University of Toronto
Zhongyuan Liu	McMaster University
Moira MacNeil	University of Toronto
Yijun Ma	McMaster University
Michael Metel	Huawei Canada
Rahul Mihir Patel	University of Toronto
Sebastian Pokutta	Technical University of Berlin and ZIB
Abdullah Ali Sivas	Huawei Technologies Canada
Michael Smith	Northern Illinois University
Christoph Spiegel	Zuse Institute Berlin (ZIB) / TU Berlin
Ian Sugrue	Northern Illinois University
Mina Torabi Milani	University of Waterloo
Fei Wang	University of Waterloo
Tyler Weames	University of Waterloo
Henry Wolkowicz	University of Waterloo
Yong Zhang	Huawei Technologies Canada
Zirui Zhou	Huawei Technologies Canada
Yuriy Zinchenko	Gurobi Inc. and University of Calgary

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Workshop on Recent Advances in Optimization

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