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Stream 1a: Nonlinear Programming I
WA196 — Nonlinear stochastic optimization
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Distributed Composite Stochastic Mirror Descent for Stochastic Optimization
Yao Ji, Purdue University -
Stochastic Adaptive Regularization Method with Cubics - A High Probability Complexity Bound
Miaolan Xie, Cornell University -
Design Guidelines of Noise-Tolerant Optimization Methods
Yuchen Lou, Northwestern University -
Robustly Learning Single-Index Models via Alignment Sharpness
Puqian Wang, University of Wisconsin, Madison
WA251 — Algebraic Methods in Nonlinear Programming
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Convex Network Flows
Theo Diamandis, MIT -
A full splitting algorithm for fractional programs with structured numerators and denominators
Min Tao, Nanjing University -
O-minimal structures and central paths in nonlinear optimization
Ali Mohammad Nezhad, University of North Carolina At Chapel Hill -
On describing convex hull of quadratic sets via aggregations
Shengding Sun, University of Cambridge
WA284 — Theory of constrained nonlinear optimization
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Complexity Guarantees for Optimal Nash Equilibrium Seeking and Bilevel Variational Inequalities
Farzad Yousefian, Rutgers University -
Global Resolution of Chance-Constrained Optimization Problems: Minkowski Functionals and Monotone Inclusions
Uday Shanbhag, Pennsylvania State University -
Breaking the cycle: Deterministic block-iterative analysis for the Frank-Wolfe algorithm
Zev Woodstock, Zuse Institute Berlin (Zib) -
Damped Proximal Augmented Lagrangian Method for weakly-Convex Problems with Convex Constraints
Yangyang Xu, Rensselaer Polytechnic Institute
Stream 1b: Global Optimization
WA831 — Global Optimization 1
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Manifolds of solutions in deterministic global optimization
Hermann Schichl, University of Vienna -
Difference-of-Convex Piecewise Linear Delta-Approximation and Its Application in Global Optimization
Xiang Li, Zhejiang University -
Location of optima and vertex optimality
Fabio Tardella, University of Florence -
An Adaptive Block Proximal ADMM for Weakly Convex, Linearly-Constrained Composite Functions
Leandro Maia, Texas A&M University
Stream 1c: Nonsmooth Optimization
WA285 — Efficient algorithms for large-scale sparse optimization problems and applications
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Convex facial reduction algorithm and strong extended dual
Ying Lin, Department of Applied Mathematics, The Hong Kong Polytechnic University -
An Accelerated Preconditioned ADMM for Solving the Optimal Transport Problem
Guojun Zhang, Department of Applied Mathematics, The Hong Kong Polytechnic University -
Collective Certified Robustness against Graph Injection Attacks
Kaihuang Chen, Department of Applied Mathematics, The Hong Kong Polytechnic University -
An efficient sieving based secant method for sparse optimization problems with least-squares constraints
Defeng Sun, The Hong Kong Polytechnic University
WA333 — Recent Advances in Regularized and Composite Optimization
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Epi-convergent approximations of discontinuous generalized eigenvalue functions with application to topology optimization
Akatsuki Nishioka, The University of Tokyo -
A Proximal Modified Quasi-Newton Method for Nonsmooth Regularized Optimization
Mohamed Laghdaf Habiboullah, Polytechnique Montréal -
Feature Selection for Linear Fixed Effects Models
James Burke, University of Washington, Seattle -
An efficient continuation algorithm for regularized optimization through the Moreau envelope
Alexander Hsu, University of Washington
Stream 1d: Semi-Definite Programming
WA97 — Semidefinite programming, sums of squares, and quantum information
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Bell nonlocality and Grothendieck constants via Frank-Wolfe algorithms
Sébastien Designolle, Zuse Institute Berlin -
A simple approximation algorithm for Quantum Max Cut via Maximum Matching
Ojas Parekh, Sandia National Laboratories -
Analysis of ncSoS relaxations for the quantum rotor model
Sujit Rao, MIT -
Relaxations and Exact Solutions to Quantum Max Cut via the Algebraic Structure of Swap Operators
Adam Bene Watts, University of Waterloo
WA208 — Low-rank semidefinite optimization, algorithms, software and applications
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Accelerating nuclear-norm regularized low-rank matrix optimization through Burer-Monteiro decomposition
Tianyun Tang, National University of Singapore -
Well-conditioned primal-dual interior-point method for accurate low-rank semidefinite programming
Hong Ming Chiu, University of Illinois Urbana Champaign -
Loraine news: From a low-rank to a high-precision SDP solver
Michal Kocvara, University of Birmingham -
An Augmented Lagrangian Primal-Dual Semismooth Newton Method for Multi-Block Composite Optimization
Zhanwang Deng, Peking University
Stream 1e: Variational Analysis, Variational Inequalities and Complementarity
WA338 — Algorithms for optimization, monotone inclusions and variational inequalities 3
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Exotic error bounds, Karamata theory and convergence rate analysis
Bruno Lourenço, Institute of Statistical Mathematics -
DEFBAL -- a connection between the ADMM and forward-backward methods
Jonathan Eckstein, Rutgers University -
The Douglas–Rachford algorithm for inconsistent problems
Bethany Caldwell, University of South Australia -
The Chambolle-Pock algorithm revisited: splitting operator and its range with applications
Walaa Moursi, University of Waterloo
Stream 1f: Random Methods for Continuous Optimization
WA334 — Random subspace methods for continuous optimization
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A Semismooth Newton Stochastic Proximal Point Algorithm with Variance Reduction
Michael Ulbrich, Technical University of Munich -
Applying Random projection techniques to large-scale nonconvex optimization problems
Akiko Takeda, The University of Tokyo / Riken -
Random projections for quadratically constrained quadratic programming
Benedetto Manca, Università Degli Studi Di Cagliari -
Random subspace Newton method for unconstrained non-convex optimization
Pierre Louis Poirion, Riken
Stream 1g: Derivative-free and Simulation-based Optimization
WA309 — Multifidelity and Bilevel DFO
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Multifidelity Monte Carlo estimates for accelerating stochastic optimization with trust regions
Yunsoo Ha, National Renewable Energy Lab -
Hierarchically constrained multi-fidelity blackbox optimization
Xavier Lebeuf, Polytechnique Montréal -
Zeroth-order bilevel optimization
Saeed Ghadimi, University of Waterloo -
Inexact direct-search methods for bilevel optimization problems
Francesco Rinaldi, University of Padova
Stream 2a: Mixed Integer Linear Programming
WA231 — Bilevel Optimization with Discrete Decisions (I)
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Playing Stackelberg Security Games in perfect and imperfect formulations
Martin Labbe, Free University of Brussels (Ulb) -
A Toll-Setting Problem with Gamma-Robust Wardrop Equilibrium Conditions
Yasmine Beck, Trier University -
BOBILib - A Bilevel Optimization Benchmark Instance Library
Martin Schmidt, Trier University -
A Branch-and-Cut Algorithm for Mixed-Integer Bilevel Linear Optimization Based on Improving Directions
Federico Battista, Lehigh University
WA842 — Mixed Integer Linear Programming 2
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Lifting of the cover inequalities for the robust knapsack problem
Youngjoo Roh, Seoul National University -
A novel Pareto-optimal cut selection strategy for Benders Decomposition
Florian Roesel, Friedrich Alexander Universität Erlangen Nürnberg -
Bulk Optimization approaches to Graph Problems
Enrico Malaguti, Dei University of Bologna -
Route 'em and Count 'em : A Two-Stage Stochastic Programming Model in Undersea Warfare
Vanessa Ann Beddoe Sawkmie, University of Wisconsin Madison
Stream 1h: Optimal Control, PDE Constrained Optimization, and Multi-level Methods
WA840 — Optimal Control, PDE Constrained Optimization, and Multi-level Methods 1
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Robust Optimal Control Through Scenario-Based Solutions to Semi-Infinite Programs With Existence Constraints
Jad Wehbeh, Imperial College London -
Towards robust optimization of chromatographic separation processes with flow reversal
Dominik H. Cebulla, Institute For Mathematical Optimization, Technische Universität Braunschweig -
Input-Output Stability of First-Order Optimization Algorithms: A Passivity Approach
Sepehr Moalemi, Mcgill University -
Image Registration Using Optimal Control of a Linear Hyperbolic Transport Equation
Johannes Haubner, University of Graz
Stream 2b: Mixed Integer Nonlinear Programming
WA8 — Mixed Integer Quadratic/Conic Optimization
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An Outer Approximation Method for Solving Mixed-Integer Convex Quadratic Programs with Indicators
Linchuan Weo, Northwestern University -
New Perspectives on Deriving Compact Extended Formulations for Optimization Problems with Indicator Variables
Fatma Kilinc Karzan, Carnegie Mellon University -
Convexification and solution of mixed-integer quadratic programs using decision diagrams
Andres Gomez, University of Southern California -
Sensitivity Analysis for Mixed Binary Quadratic Programs
Santanu Dey, Georgia Institue Of Technology
Stream 2c: Combinatorial Optimization and Graph Theory
WA169 — Complexity and algorithmic aspects of structured families of graphs 2
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Reconfiguration of Vertex Colourings in Hereditary Classes of Graphs
Kathie Cameron, Wilfrid Laurier University -
Gallai-like characterization of strong cocomparability graphs
Jing Huang, University of Victoria -
On Mixed Cages
M. Gabriela Araujo Pardo, Math Institute, Universidad Nacional Autónoma De México -
Complexity dichotomies for list homomorphism problems of signed graphs
Jan Bok, Charles University
WA849 — Combinatorial Optimization and Graph Theory 3
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The betweenness model for the single-row facility layout problem and beyond
Anja Fischer, Tu Dortmund University -
Envy-free Pricing of Seats in a Planetarium
Freija Van Lent, Maastricht University -
Finding Maximum Edge-Disjoint Paths Between Multiple Terminals
Satoru Iwata, University of Tokyo -
Packing Hypertrees and the k-cut problem in hypergraphs
Francisco Barahona, IBM Research
Stream 2d: Machine Learning and Discrete Optimization
WA853 — Machine Learning and Discrete Optimization 1
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Gurobi Machine Learning
Roland Wunderling, Gurobi -
Wasserstein Distributionally Robust Shallow Convex Neural Networks
Julien Pallage, Polytechnique Montréal -
Machine Learning for Distributionally Robust Warm-Starting in Mineral Supply/Value Chains
Yassine Yaakoubi, Mcgill University -
A machine learning approach for neighbor generation in metaheuristic search
Defeng Liu, Polytechnique Montreal
Stream 2e: Approximation and Online Algorithms
WA857 — Approximation and Online Algorithms 2
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Scheduling with Obligatory Tests
Thomas Erlebach, Durham University -
An Exact Method for the Job Sequencing and Tool Switching Problem
Alberto Locatelli, University of Modena And Reggio Emilia -
Recent progress for correlation clustering
Alantha Newman, CNRS Université Grenoble Alpes -
Approximating large-scale Hessian matrices using secant equations
Jaroslav Fowkes, Science And Technology Facilities Council
Stream 2f: Computational Discrete and Integer Optimization
WA281 — New Algorithms for Large-Scale Optimization
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Dynamic constraint aggregation for solving the minimum sum-of-squares clustering problem
Antonio M. Sudoso, Sapienza University of Rome -
Generalized integral simplex
Alpha Saliou Barry, Polytechnique Montréal -
Integral Simplex for the Set Partitioning Problem
Francois Soumis, Polytechnique Montreal University -
New complementary problem formulation for the improved primal simplex
Youssouf Emine, GERAD
Stream 2g: Constraint Programming
WA243 — Constraints and Machine Learning
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Optimal counterfactual explanations for k-Nearest Neighbors using Mathematical Optimization and Constraint Programming
Ricardo Fukasawa, University of Waterloo -
MORBDD: Multiobjective Restricted Binary Decision Diagrams by Learning to Sparsify
Rahul Patel, University of Toronto -
Learning Lagrangian Multipliers for the Travelling Salesman Problem
Louis Martin Rousseau, Polytechnique Montréal -
Constraint Learning to Define Trust Regions in Optimization Over Pre-Trained Predictive Models
Chenbo Shi, University of Connecticut
Stream 3a: Continuous Stochastic Programming
WA102 — Multistage Optimization Programs under Uncertainty
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Multistage distributional robustness, time consistency and optimal policy
Rui Gao, University of Texas at Austin -
Distributionally robust chance-constrained Markov decision processes
Abdel Lisser, University Paris Sacaly, Centralesupelec -
Risk Evaluation and Control for Distributed Multi-Agent Systems
Darinka Dentcheva, Stevens Institute of Technology
Stream 3b: Discrete Stochastic Programming
WA58 — Stochastic Integer Programming: Models and Algorithms
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Master Surgery Scheduling Problem Considering Uncertainty in Time of Stay in Downstream Units; A Matheuristic Solution Approach
Erfaneh Nikzad, Polytechnique Montréal -
Probing-Enhanced Stochastic Programming
Jeff Linderoth, University of Wisconsin Madison -
The Chance-constrained Stochastic Diversion Path Problem with Sample Average Approximation
Woojin Kim, University of Wisconsin Madison -
Stochastic facility location problem with outsourcing costs
Eduardo Moreno, Universidad Adolfo Ibanez / Google France
Stream 3c: Robust and Distributionally Robust Optimization
WA106 — Robust Optimization and Machine Learning 3
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On Foundations of Distributionally Robust Reinforcement Learning
Jose Blanchet, Stanford University -
Regularization for Adversarial Robust Learning
Jie Wang, Georgia Institute of Technology -
Distributionally Robust Affine Markov Decision Processes
Karthyek Murthy, Singapore University of Technology And Design -
Enhancing Data-Driven Distributionally Robust Optimization: Jointly Incorporating First-Order Moment and Wasserstein Distance
Caihua Chen, Chchen@Nju.Edu.Cn
Stream 3d: Multi-stage Stochastic Programming and Reinforcement learning
WA148 — Advances in Approximate Dynamic Programming with Energy Applications
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Network dual reoptimization policies and bounds for managing energy real options
Alessio Trivella, University of Twente -
Reinforcement Learning for Energy-Efficient Job Shop Scheduling with Large Structured Action Spaces
Wouter Van Heeswijk, Universiteit Twente -
Stochastic Approximation for Upper Bound Optimization in Markov Decision Processes
Negar Soheili, University of Illinois At Chicago -
Reinforcement Learning or Policy Sampling: An Online Coupling Policy with an Energy Storage Application
Stephan Meisel, University of Twente
Stream 3e: Data-driven optimization
WA866 — Data-driven optimization 1
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A Tractable Online Learning Algorithm for the Multinomial Logit Contextual Bandit
Priyank Agrawal, Columbia University -
Smoothness-Adaptive Dynamic Pricing with Nonparametric Demand Learning
Hansheng Jiang, University of Toronto -
A Benders Decomposition Algorithm for the Overland Search and Rescue Problem Considering Search Area Selection
Saeid Abbasiparizi, Ph.D. Student At Department of Operations And Decision Systems, Université Laval, Québec, Canada -
Stochastic gradient methods with adaptive learning rates
Adrian Riekert, University of Münster
Stream 4b: Transportation and logistics
WA872 — Transportation and logistics 3
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A two-stage stochastic programming model with recourse for a Production Routing Problem with uncertain availability of vehicles
Michel Gendreau, CIRRELT And MAGI, Polytechnique Montréal -
Generalized Dial-A-Ride Problem on Road Networks with Time-dependent Travel Times
Bahman Bornay, CIRRELT And MAGI, Polytechnique Montréal -
A Stochastic Approach for Mobile Clinic Deployment Planning
Rosemarie Santa, Georgia Institute of Technology -
A column generation approach for the routing of electricity technicians
David Schindl, University of Applied Sciences Western Switzerland, Heg Genève
Stream 4d: Energy and Environment
WA206 — Equilibrium modeling in energy markets
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Equilibrium Modeling in Natural Gas Markets: A Theoretical Analysis and a Case Study for Brazil, A Method for Solving Gas Market and Water Market Equilibrium Problems
Steven Gabriel, University of Maryland -
When market incompleteness is preferable to market power. Insights from power markets.
Ibrahim Abada, Grenoble Ecole de Management -
Connection queues and shared connection costs
Eddie Anderson, Imperial College -
Analysis of ISO New England's Energy Imbalance Reserve Using Mixed Complementarity Problems
Ryan Ent, University of Massachusetts Amherst
WA882 — Energy and Environment 2
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Using structural properties to optimize operating strategies of district heating networks under nonlinear constraints
Rehlich Lea, Tu Darmstadt -
Obtaining the Convex Hull Formulation for Optimal Investment and Operation of Energy Storage Systems Including Reserves
Maaike Elgersma, Delft University of Technology -
A Convex Model Predictive Control Optimization Model of Active Distribution Network Flexibility Regions
Luis Lopez, Phd Student -
Smart Grids, Smart Pricing: Employing Reinforcement Learning for Prosumer-Responsive Critical Peak Pricing
Seyyedreza Madani, HEC Montréal
Stream 4g: High performance implementation and quantum computing
WA191 — Optimization Modeling
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Steepest-edge simplex algorithms for quadratic programming
Shoji Shimizu, NTT Data Mathematical Systems Inc. -
An imitation-based learning approach using DAgger for the Casual Employee Call Timing Problem
Prakash Gawas, Polytechnique Montreal -
From Algorithms to Applications: developing and deploying analytical and optimization models with FICO® Xpress Insight
Bruno Vieira, Fico -
OMLT: Solving inverse problems over trained graph neural networks
Ruth Misener, Imperial College London
Stream 4i: Industrial applications
WA273 — Large Scale Supply-Chain Network Design II
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Multi-Modeling Approach to Real-World Optimization Problems
Eugene Zak, Independent Consultant -
A decomposition approach for large scale service network design
Arash Haddadan, Amazon -
Practical stochastic network design for long-term network planning
David Mildebrath, Amazon -
Velocity-aware inventory placement
R Ravi, Amazon Scholar
Stream 5c: Special sessions
WA316 — In memory of Jean-Louis Goffin 1: Recent advances in large scale optimization
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Lifting nonnegativity over general semialgebraic sets to nonnegativity over simple sets
Luis Zuluaga, Lehigh University -
A low-rank method for large-scale semidefinite programs
Renato Monteiro, Georgia Tech -
Rectified relaxation: A trustworthy and interpretable deep learning approach to linear optimization with complementary constraints
Jiming Peng, University of Houston