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Stream 1a: Nonlinear Programming I
FB75 — The interplay between optimization, statistics and machine learning II

AdaBB: A ParameterFree Gradient Method for Convex Optimization
Shiqian Ma, Rice University 
Kernel Learning in Ridge Regression “Automatically” Yields Exact Low Rank Solution
Feng Ruan, Northwestern University 
Overparameterized Tensor Regression via Riemannian Optimization
Yuetian Luo, University of Chicago 
The BurerMonteiro SDP method can fail even above the BarvinokPataki bound
Vaidehi Srinivas, Northwestern University
FB154 — Firstorder Methods and Largescale Optimization III

Inexact restoration for minimization with inexact evaluation both of the objective function and the constraints
L Felipe Bueno, Federal University of São Paulo 
A Generalized Version of Chung’s Lemma and its Applications
Li Jiang, The Chinese University of Hong Kong, Shenzhen 
On the Trajectories of SGD Without Replacement
Pierfrancesco Beneventano, Princeton University 
Revisiting the LastIterate Convergence of Stochastic Gradient Methods
Zijian Liu, New York University
FB114 — Computational advancement in nonconvex programming

EM Algorithms for Optimization Problems with Polynomial Objectives
Jun Ya Gotoh, Chuo University 
Level constrained firstorder methods for nonconvex function constrained optimization
Digvijay Boob, Southern Methodist University 
Methods of DifferenceofConvex Programming for Statistical Learning with Structured Sparsity
Miju Ahn, Southern Methodist University 
GPU Implementation of Algorithm NCL
Alexis Montoison, GERAD
FB70 — Nonlinear Programming for Data Science II

High order stochastic optimization without evaluating the function.
Serge Gratton, University of Toulouse, Inp, Irit, Aniti 
Randomized matrix decompositions for faster scientific computing
Robert Webber, California Institute of Technology 
Adaptive Stochastic Optimization with Constraints
Mladen Kolar, University of Chicago 
Random subspace second order methods for nonconvex optimization
Edward Tansley, University of Oxford
Stream 1b: Global Optimization
FB1 — Recent Advances in Global Optimization of Nonconvex Programs

Discretization Approaches for NonConvex MixedInteger Nonlinear Programs
Robert Burlacu, University of Technology Nuremberg 
Constructing Tight Quadratic Underestimators for Global Optimization
Arvind Raghunathan, Mitsubishi Electric Research Laboratories 
A Generalizable EndtoEnd Learning Approach for Global Optimization of QuadraticallyConstrained Quadratic Programs
Erin George, Ucla Mathematics 
Piecewise Polyhedral Relaxations of Multilinear Optimization
Mohit Tawarmalani, Purdue University
Stream 1c: Nonsmooth Optimization
FB257 — Complexity of Stationarity Concepts in NonSmooth Optimization

Testing Approximate Stationarity Concepts for Piecewise Affine Functions
Lai Tian, The Chinese University of Hong Kong 
Strong Secondorder Sufficient Condition of Decomposable Functions
Wenqing Ouyang, The Chinese University of Hongkong (Shenzhen) 
Nonsmooth NonconvexNonconcave Minimax Optimization: PrimalDual Balancing and Iteration Complexity Analysis
Linglingzhi Zhu, The Chinese University of Hong Kong
Stream 1d: SemiDefinite Programming
FB275 — Recent Advancements in the Theory and Applications of Semidefinite Programming

Navigating hidden convexity in nonconvex projection problems
Manish Krishan Lal, UBC 
The Maximum Singularity Degree for Linear and Semidefinite Programming
Hao Hu, Clemson University 
Ramana's dual redux
Gabor Pataki, UNC Chapel Hill 
A PeacemanRachford Splitting Method for the Protein SideChain Positioning Problem and other Hard Problems
Henry Wolkowicz, University of Waterloo
FB36 — SDP and Exact Relaxations of Hard Problems

ForwardBackward Extended DMD with an Asymptotic Stability Constraint
Louis Lortie, Mcgill University 
Convex conic reformulation of geometric nonconvex conic optimization problems and exact solutions of QCQPs by SDP relaxations
Sunyoung Kim, Ewha W. Univ. 
On the tightness of SDP relaxation for quadratic assignment problem
Shuyang Ling, NYU Shanghai 
Highrank Solution of SumofSquares Relaxations for Exact Matrix Completion
Godai Azuma, Aoyama Gakuin University
Stream 1e: Variational Analysis, Variational Inequalities and Complementarity
FB336 — Nonsmooth and hierarchical optimization in machine learning

Firstorder methods for bilevel optimization
Zhaosong Lu, University of Minnesota 
Classification under strategic adversary manipulation using pessimistic bilevel optimisation
David Benfield, University of Southampton 
A Banachspace view of neural network training
Rahul Parhi, UCSD
Stream 1f: Random Methods for Continuous Optimization
FB52 — Splitting and Randomized Methods 4

A Recursive Multilevel Algorithm for Deep Learning
Isabel Jacob, Technical University Darmstadt 
Improved variance reduction extragradient method with line search for stochastic variational inequalities
Ting Li, Beihang University 
Differentially Private Federated Learning via Inexact ADMM with Multiple Local Updates
Jingya Chang, Guangdong University of Technology
Stream 1g: Derivativefree and Simulationbased Optimization
FB327 — Stochastic DFO 2

Stochastic derivativefree optimization algorithms using random subspace strategies
Kwassi Joseph Dzahini, Argonne National Laboratory 
Nonconvergence analysis of probabilistic direct search
Zaikun Zhang, The Hong Kong Polytechnic University 
Fulllow evaluation methods for bound and linearly constrained derivativefree optimization
Clément Royer, Université Paris Dauphine Psl 
Expected decrease for derivativefree algorithms using random subspaces
Clement Royer, Paris Dauphine
Stream 2a: Mixed Integer Linear Programming
FB151 — Recent Developments in MIP Theory and Applications

Proximity results in conic mixedinteger programming
Burak Kocuk, Sabanci University 
On formulations of the closeenough TSP
Gustavo Angulo, Pontificia Universidad Católica De Chile 
A ConvexificationBased OuterApproximation Method for Convex and Nonconvex MINLP
David Bernal Neira, Purdue University 
MDecomposable Sets in Integer Programming
Diego Alejandro Moran Ramirez, Rensselaer Polytechnic Institute
FB919 — Mixed Integer Linear Programming 5

Generalized Cuts and Grothendieck Covers: Algorithmic Performance
Nathan Benedetto Proença, University of Waterloo 
Combinatorial solving with provably correct results
Jakob Nordström, University Copenhagen
Stream 2b: Mixed Integer Nonlinear Programming
FB9 — Theory of Mixed Integer Nonlinear Programming

Complexity of Mixed Integer Nonlinear Programming with Nonconvexities
Robert Hildebrand, Virginia Polytechnic Institute And State University 
A Knowledge Compilation Take on Binary Polynomial Optimization
Silvia Di Gregorio, Université Sorbonne Paris Nord 
On the power of linear programming for data clustering
Aida Khajavirad, Lehigh University 
Sample Complexity and Computational Results for Branch and Cut Using Neural Networks
Barbara Anna Fiedorowicz, Johns Hopkins University
Stream 2c: Combinatorial Optimization and Graph Theory
FB926 — Combinatorial Optimization and Graph Theory 6

Bounding the Proper Orientation Number by Treedepth
Hirotaka Ono, Nagoya University 
Beam Search to Minimise Cutting Patterns with Maximum Utilisation
Claudia O López Soto, National Autonomous University of Mexico (Unam) 
3D Phase Unwrapping using 3D Surface minimization.
El Mehdi Oudaoud, Polytechnique Montreal 
Uncrossable Multicommodity Flows
Joseph Poremba, The University of British Columbia
Stream 2d: Machine Learning and Discrete Optimization
FB929 — Machine Learning and Discrete Optimization 3

FASTopt: An Optimization Framework for Fast Additive Segmentation in Transparent ML
Brian Liu, MIT 
Reliability evaluation of gaussian processes applied to power systems
Pierre Houdouin, RTE France 
Closedloop Koopman operator approximation
Steven Dahdah, Mcgill University 
Novel MixedInteger Optimization Approaches for Interpretable SVMs
Federico D'onofrio, Sapienza University of Rome
Stream 2e: Approximation and Online Algorithms
FB295 — Algorithms with Predictions

Fair Secretaries with Unfair Predictions
Eric Balkanski, Columbia University 
Incremental Topological Ordering and Cycle Detection with Predictions
Benjamin Moseley, Carnegie Mellon University 
Algorithms with Prediction Portfolios
Thomas Lavastida, The University of Texas at Dallas 
EnergyEfficient Scheduling with Predictions
Clifford Stein, Columbia University
FB225 — Fairness via Optimization Modeling and Approximation Algorithms

Improved Approximation Algorithms for the Joint Replenishment Problem with Outliers, and with Fairness Constraints
Varun Suriyanarayana, Cornell University 
Assortment Optimization with Visibility Constraints
Marouane Ibn Brahim, Cornell Tech 
Fairness, Randomization, and Approximation Algorithms
Aravind Srinivasan, University of Maryland 
Algorithmic Tools for Redistricting: Fairness via Analytics
David Shmoys, Cornell University
Stream 2f: Computational Discrete and Integer Optimization
FB268 — Integer Programming Applications in Mobility and Traffic

On the Split Closure of the Periodic Timetabling Polytope
Niels Lindner, Freie Universität Berlin 
Integrated Periodic Event Scheduling and Infrastructure Assignment: approaches via Cyclic Orders and Graph Matchings
Enrico Bortoletto, Zuse Institute Berlin 
A Flexible Model for Integrated Line Planning and Periodic Timetabling with Track Choice in Practice
Berenike Masing, Zuse Institute Berlin 
The Approximation Error Caused by Linearizing Charging Behavior for Electric Vehicle Scheduling Problems
Fabian Löbel, Zuse Institute Berlin
Stream 2g: Constraint Programming
FB242 — Learning and Explaining Constraints

DomainIndependent Dynamic Programming
J. Christopher Beck, University of Toronto 
Lazy MIP Solving with Methods from SAT
Alexander Tesch, Bool AI 
Automated Streamlining for Constraint Satisfaction Problems.
Ian Miguel, University of St Andrews 
QueryBased Constraint Acquisition
Nadjib Lazaar, LIRMM, University of Montpellier, CNRS
Stream 3a: Continuous Stochastic Programming
FB936 — Continuous Stochastic Programming 3

Stable Matching with Contingent Priorities
Federico Bobbio Bobbio, University of Montreal 
On the ChanceConstrained Optimization with Gaussian Mixture Models
Shibshankar Dey, Industrial Engineering And Management Sciences, Northwestern University
Stream 3c: Robust and Distributionally Robust Optimization
FB184 — Exact methods for robust nonlinear optimization

RPT for robust nonlinear optimization problems
Danique De Moor, Massachusetts Institute of Technology 
ReformulationPerspectification Technique for problems with conic uncertainty sets
Dick Den Hertog, University of Amsterdam 
An exact method for a class of robust nonlinear optimization problems
Thororis Koukouvinos, Operations Research Center, Massachusetts Institute of Technology, United States
FB104 — Datadriven Robust Optimization

Conformal Inverse Optimization
Bo Lin, University of Toronto 
Learning DecisionFocused Uncertainty Sets in Robust Optimization
Irina Wang, Princeton University 
Neur2RO: Neural TwoStage Robust Optimization
Justin Dumochelle, University of Toronto
FB122 — Optimization with Marginals and Moments

Distributionally robust optimization through the lens of submodularity
Karthik Natarajan, Singapore University of Technology And Design 
When submodularity meets pairwise independence
Arjun Ramachandra, IIM Bangalore 
Convex Optimization for Bundle Size Pricing Problem
Hailong Sun, Antai College Of Economics And Management, Shanghai Jiao Tong University 
Progresses in Modeling and solving distributional robust optimization problems
He Simai, Shanghai Jiao Tong University
Stream 3d: Multistage Stochastic Programming and Reinforcement learning
FB109 — Advances in multistage stochastic programming

MultiStage Stochastic Programming for Integrated Hurricane Evacuation and Logistics Planning
Yongjia Song, Clemson University 
Multistage ChanceConstrained Programming
Hamed Rahimian, Clemson University 
Interpretable Vaccine Administration and Inventory Replenishment Policies via SmoothinExpectation Decision Rules
Merve Bodur, University of Edinburgh 
Solving multistage equilibrium problems: the KrusellSmith model
Bernardo Pagnoncelli, Skema Business School
Stream 3e: Datadriven optimization
FB141 — Advances in datadriven decision making

Learning Optimal Classification Trees Robust to Distribution Shifts
Nathan Justin, University of Southern California 
Randomized Nyström Preconditioned Interior PointProximal Method of Multipliers (IPPMM)
Ya Chi Chu, Stanford University 
On the Equivalence and Performance of Distributionally Robust Optimization and Robust Satisficing Models in OM Applications
Long He, George Washington University 
Randomized policy optimization for highdimensional optimal stopping
Velibor Misic, Ucla
Stream 4b: Transportation and logistics
FB172 — Demandbased and stochastic urban transportation planning

Competing on Emissions Charges
Gianmarco Andreana, University of Bergamo 
Hub Transportation Problem with Chance Constrained Due Dates
Öykü Naz Attila, Polytechnique Montreal 
Collaborative Optimization of Rolling Stock Allocation and Timetable Coordination in a MultiModal Rail Network: MILP Formulation and DecompositionBased Algorithm
Jiateng Yin, Beijing Jiaotong University 
A Reinforcement Learning Approach for Dynamic Rebalancing in BikeSharing Systems
Jiaqi Liang, Polytechnique Montreal
FB164 — Humanitarian Logistics

A Mutual Catastrophe Insurance Framework for Horizontal Collaboration in Prepositioning Strategic Reserves
Hani Zbib, University of Quebec In Montreal 
Mitigating fire risk towards critical and residential structures near a high ignition area using Critical Node Detection
Vittorio Nicoletta, HEC Montréal 
The Value of Demand Prediction for Improved Food Security
Alborz Hassanzadeh, HEC Montréal 
A bilevel optimization approach for shelter network design and evacuation planning problem: An application to flood preparedness in Haiti
Maedeh Sharbaf, HEC Montréal
Stream 4d: Energy and Environment
FB959 — Energy and Environment 4

Efficient hydrogen infrastructure design using JuMP and convex approximations
Truls Flatberg, SINTEF 
Applications of Optimization in Land Conservation
Hande Benson, Drexel University
Stream 4g: High performance implementation and quantum computing
FB165 — A glimpse of computational optimization at Google III

ViolationLS: ConstraintBased Local Search in CPSAT
Toby Davies, Google 
MathOpt: Solver independent modeling and execution independent solving in Google's ORTools
Ross Anderson, Google 
Google's Operations Research API
Daniel Duque, Google 
Duality and decomposition in ORTools' MathOpt
Juan Pablo Vielma, Google
Stream 5c: Special sessions
FB821 — Friday

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