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Stream 1c: Nonsmooth Optimization
ThB54 — Projection-free first-order methods for convex optimization
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Saddle-point Frank-Wolfe methods for Linear Programming
Stephen Vavasis, University of Waterloo -
The Generalized Multiplicative Gradient Method for a Class of Convex Symmetric Cone Optimization Problem
Renbo Zhao, University of Iowa -
Adaptive Open-Loop Step-Sizes for Accelerated Frank-Wolfe Convergence
Elias Wirth, Tu Berlin -
Affine-invariant convergence of Frank-Wolfe algorithms on polytopes
Javier Pena, Carnegie Mellon University
ThB907 — Nonsmooth Optimization 2
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An abstract convergence framework with application to proximal Heavy-ball line-search algorithms
Simone Rebegoldi, University of Modena And Reggio Emilia -
On the limit form of the Su-Boyd-Candès dynamic version of Nesterov's accelerated gradient method when the viscous parameter becomes large
Samir Adly, University of Limoges -
Inertial Accelerated Stochastic Mirror Descent for Large-Scale Generalized Tensor CP Decomposition
Zehui Liu, Beihang University -
** CANCELLED ** Convergence of the momentum method for semialgebraic functions with locally Lipschitz gradients
Cedric Josz, Columbia University
Stream 1a: Nonlinear Programming I
ThB37 — Sum-of-squares methods for continuous optimization and beyond
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GloptiNets: Scalable Non-Convex Optimization with Certificates
Gaspard Beugnot, INRIA -
Convex relaxations for Gibbs states
Hamza Fawzi, University of Cambridge -
Moment-SOS relaxations for variational problems
Giovanni Fantuzzi, Fau Erlangen Nürnberg -
Nonconvergence of some sum-of-squares bounds for global polynomial optimization
Lucas Slot, ETH Zurich
ThB137 — First-order Methods and Large-scale Optimization II
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Adaptivity in convex optimization beyond minimization
Puya Latafat, KU Leuven -
The Anytime Convergence of Stochastic Gradient Descent with Momentum: From a Continuous-Time Perspective
Yasong Feng, Fudan University -
Efficient sparse probability measures recovery via Bregman gradient
Jianting Pan, The Chinese University of Hong Kong, Shenzhen -
Universal heavy-ball method for nonconvex optimization under Hölder continuous Hessians
Naoki Marumo, University of Tokyo
ThB93 — Nonconvex optimization: landscapes and dynamics I
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The sensor network localization problem has benign landscape under mild rank relaxation
Christopher Criscitiello, EPFL -
Stochastic approximation with decision-dependent distributions: asymptotic normality and optimality
Mateo Diaz, Johns Hopkins University -
Synchronization on circles and spheres with nonlinear interactions
Nicolas Boumal, EPFL -
Symmetry and Critical Points
Yossi Arjevani, The Hebrew University
ThB35 — Nonlinear Programming for Data Science I
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Reliable Optimization Algorithms when Objective Function Evaluations are Expensive
Vivak Patel, University of Wisconsin Madison -
Yet another fast variant of Newton's method for nonconvex optimization
Philippe Toint, University of Namur (Past) -
Approximate Derivatives for Tensor Methods
Karl Welzel, University of Oxford -
Deterministic and Stochastic Frank Wolfe Recursion on Probability Spaces
Raghu Pasupathy, Purdue University
Stream 1b: Global Optimization
ThB26 — Large-Scale and Structured Optimization
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A procedure for listing KKT points of a quadratic reverse convex programming problem
Syuuji Yamada, Niigata University -
Continuous Approaches to Discrete Optimization Problems
Miltiades Pardalos, Texas A&M University -
Viral Quasispecies Analysis via Tensor Factorization
Qian Zhang, Singapore University of Technology And Design -
Projection-Free Methods for Solving Convex Bilevel Optimization Problems
Nam Ho Nguyen, The University of Sydney
Stream 1d: Semi-Definite Programming
ThB123 — Online optimization and learning in quantum games
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A Semi-Definite Programming Approach for the Single-Row Facility Layout Problem with Multiple Objectives
Christof Brandstetter, Johannes Kepler University -
Semidefinite Network Games
Constantin Ickstadt, Goethe University Frankfurt, Germany -
Learning in Quantum Potential Games
Wayne Lin, Singapore University of Technology And Design -
A Quadratic Speedup in Finding Nash Equilibria of Quantum Zero-Sum Games
Emmanouil Vasileios Vlatakis Gkaragkounis, UC Berkeley
ThB910 — Semi-Definite Programming 3
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Superlinear convergence of an interior point algorithm on linear semi-definite feasibility problems
Chee Khian Sim, University of Portsmouth -
From SDPs to polynomial equations: validating numerical solutions for semidefinite programming.
Jeferson Zapata, Institute of Science And Technology Of Austria -
Term-sparse polynomial optimization for the design of frame structures
Marouan Handa, Postdoc -
Nonsmooth Newton Methods for Solving the Best Approximation Problem; with Applications to Linear Programming
Tyler Weames, University of Waterloo
Stream 1e: Variational Analysis, Variational Inequalities and Complementarity
ThB226 — Nonconvexity, stochasticity and hierarchy in optimization problems
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The inexact power augmented Lagrangian method for constrained nonconvex optimization
Alexander Bodard, KU Leuven -
A quasi-Newton method for nonsmooth, nonconvex, stochastic optimization
Luke Marrinan, Penn State University -
Zeroth-order federated methods for stochastic MPECs and nondifferentiable nonconvex hierarchical optimization
Yuyang Qiu, Rutgers University -
Hessian barrier algorithms for non convex conic optimization
Mathias Staudigl, University of Mannheim
ThB913 — Variational Analysis, Variational Inequalities and Complementarity 3
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Calm local optimality for nonconvex-nonconcave minimax problems
Xiaoxiao Ma, University of Victoria -
On desingularizing functions in convex programming
Abderrahim Jourani, Institut De Mathematiques De Bourgogne, Universite De Bourgogne
Stream 1f: Random Methods for Continuous Optimization
ThB50 — Splitting and Randomized Methods 2
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Uniform Function Estimators in Reproducing Kernel Hilbert Spaces, with applications in stochastic optimization
Alois Pichler, University of Technology Chemnitz -
Data-Driven Minimax Optimization with Expectation Constraints
Xudong Li, Fudan University -
A Scalable Optimization Approach for the Multilinear System Arising from Scattered Data Interpolation
Yannan Chen, South China Normal University
Stream 1g: Derivative-free and Simulation-based Optimization
ThB300 — Stochastic DFO 1
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Convergence analysis of CMA-ES
Armand Gissler, Ecole Polytechnique -
Q-fully quadratic modeling and its application in a random subspace derivative-free method
Yiwen Chen, University of British Columbia -
A new two-dimensional model-based subspace method for large-scale unconstrained derivative-free optimization: 2D-MoSub
Yi Zhang, Institute of Computational Mathematics And Scientific/Engineering Computing -
Noise-aware derivative-free optimization
Matt Menickelly, Argonne National Laboratory
Stream 1h: Optimal Control, PDE Constrained Optimization, and Multi-level Methods
ThB318 — Shape Optimization
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Level Set-Based Topology Optimization Of 3D Magnetic Circuits With Mechanical Constraints
Zakaria Houta, ENSEEIHT Laplace, Univeristy Of Toulouse -
PDE constrained shape optimization in the space of piecewise-smooth shapes
Kathrin Welker, Tu Bergakademie Freiberg -
Mesh Denoising and Inpainting using the Total Variation of the Normal and a Shape Newton Approach
Roland Herzog, Heidelberg University -
Robust Optimization of Electric Machines: A Gradient-Based Approach for Parameter and Shape with Isogeometric Analysis
Theodor Komann, Tu Darmstadt
Stream 2a: Mixed Integer Linear Programming
ThB161 — Advances in ILP: Branch and cut
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Super-Polynomial Lower Bounds for Branch-and-Bound with General Disjunctions via Interpolation
Marc Pfetsch, Tu Darmstadt -
Compressing Branch-and-Bound Trees
Joseph Paat, University of British Columbia -
Polyhedrality made easy: Using general cut operators to determine when cut closures are polyhedral
Antonia Chmiela, Zuse Institute Berlin -
Learning to Generate Cutting Planes with MIPLearn
Alinson Santos Xavier, Argonne National Laboratory
ThB918 — Mixed Integer Linear Programming 4
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Strong Cutting Planes for the Feature Selection Problem
Renaud Chicoisne, Université Clermont Auvergne / Limos -
The undirected circular facility layout problem
Louisa Schroeder, Tu Dortmund University -
Inexact Flow Decomposition in Quasispecies Network via Integer Linear Programming
Fernando Dias, Aalto University -
Production scheduling of open pit mines using new cutting planes
Venkat Akhil Ankem, Polytechnique Montreal, GERAD
Stream 2b: Mixed Integer Nonlinear Programming
ThB34 — Advances on Multi-Objective and Separable Mixed Integer Nonlinear Programming
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Pareto LEAP: An Algorithm for Biobjective Mixed Integer Nonlinear Programming
Philip De Castro, Clemson University -
Pseudo enclosures for multi-objective mixed-integer nonconvex optimization
Moritz Link, Universität Konstanz -
Detecting the integer efficient assignments for multiobjective mixed-integer convex quadratic problems
Daniele Patria, Sapienza, University of Rome -
MWU 2.0 with approximation guarantee for non-convex separable problems
Luca Mencarelli, Università Di Pisa
Stream 2c: Combinatorial Optimization and Graph Theory
ThB352 — Integer/Linear Optimisation
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Enumerating full binary trees in polynomial delay
Yasuko Matsui, Tokai University -
Optimizing over Path-Length Matrices of Unrooted Binary Trees
Daniele Catanzaro, Core Université Catholique De Louvain -
Breaking the quadratic gap for strongly polynomial solvers to combinatorial linear programs
Bento Natura, Georgia Tech -
A strongly polynomial algorithm for the minimum cost generalized flow problem
Zhuan Khye Koh, Centrum Wiskunde & Informatica
Stream 2d: Machine Learning and Discrete Optimization
ThB200 — Scaling Sparse Machine Learning
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Projection onto a Capped Rotated Second-Order Cone with Applications to Sparse Regression Relaxations
Ishy Zagdoun, Bar Ilan University -
Inexact Stochastic Proximal Methods for Sparse Group Structure Identification
Guanyi Wang, National University of Singapore -
On the power of greedy local search for sparse statistical problems
Ilias Zadik, Yale University -
Logic Rules and Chordal Graphs for Sparse Learning
Anna Deza, UC Berkeley
Stream 2e: Approximation and Online Algorithms
ThB244 — Advanced algorithms for chip design
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Depth Optimization in Binary Addition
Susanne Armbruster, University of Bonn -
Tighter Approximation for the Uniform Cost-Distance Steiner Tree Problem
Stephan Held, University of Bonn -
Resource Sharing revisited: Local weak duality and optimal convergence
Daniel Blankenburg, University of Bonn -
Decision-guided SAT for hard routing problems
Jan Malte Schürks, University of Bonn
Stream 2f: Computational Discrete and Integer Optimization
ThB342 — Combinatorial Optimization and Applications
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** CANCELLED ** Branch and Price for the Length-Constrained Cycle Partition Problem
Mohammed Ghannam, Zuse Institute Berlin -
Cutting planes for the maximum k-vertex cover problem
Sheng Jie Chen, Academy Of Mathematics And Systems Science, Chinese Academy Of Sciences -
Quota Steiner Tree Problem and its application on Wind Farm Planning
Jaap Pedersen, Zuse Institute Berlin -
A New Class of Compact Formulations for Vehicle Routing Problems
Julian Yarkony, Optym
Stream 3b: Discrete Stochastic Programming
ThB124 — Sequential Decision Making Under Uncertainty
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Online Decision Making with Nonconvex Local and Convex Global Constraints
Rui Chen, Cornell University -
Value of Stochastic Solution with Right-Hand Side Uncertainty
Haoming Shen, University of Arkansas -
Regularized MIP Model for Optimal Power Flow with Energy Storage Systems and its Applications
Dahye Han, Georgia Institute of Technology -
Two-sided assortment optimization: Adaptivity gaps and approximation algorithms
Alfredo Torrico, Cornell University
Stream 3a: Continuous Stochastic Programming
ThB935 — Continuous Stochastic Programming 2
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Duality in Optimal Stopping
Nicolas Gagné, Université De Montréal -
Adaptive Partitioning for Chance-Constrained Problems with Finite Support
Marius Roland, Polytechnique Montréal -
Consistent Assortment Optimization under the MNL with Exogenous Data
Carlos Cardonha, University of Connecticut, School Of Business -
Strong Duality in Risk-Constrained Nonconvex Functional Programming
Dionysis Kalogerias, Yale University
Stream 3c: Robust and Distributionally Robust Optimization
ThB296 — Distributionally Robust Optimization: Theory Meets Applications
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Two-Stage Distributionally Robust Optimization for Service Region Design in Crowdsourced Delivery
Aliaa Alnaggar, Toronto Metropolitan University -
Reliable Facility Location with Wasserstein Ambiguity
Kanglin Liu, Beijing Jiaotong University -
Distributionally Robust Optimization of Probability of Exceedance
Hoang Nam Nguyen, George Washington University -
Smooth Uncertainty Sets: Dependence of Uncertain Parameters via a Simple Polyhedral Set
Noam Goldberg, Bar Ilan University
Stream 3d: Multi-stage Stochastic Programming and Reinforcement learning
ThB186 — Efficient RL: Adaptive Experimentation and Estimation
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** CANCELLED ** Stochastic Programming Without Assuming a Probability Distribution
David Woodruff, Uc Davis -
Bayesian Reinforcement Learning with Limited Evaluations and Nonlinear Objectives
Somayeh Moazeni, Stevens Institute of Technology -
Planning Adaptive Experiments with Model-Predictive Control
Ethan Che, Columbia Business School -
Sample efficient estimation of the transition kernels of controlled Markov chains
Imon Banerjee, Northwestern University
Stream 3e: Data-driven optimization
ThB194 — Learning and Calibration in Data-Driven Optimization
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Service Oriented Considerate Routing: Data, Predictions and Robust Decisions
Melvyn Sim, NUS Business School -
Directional Gradients and Surrogate Losses in the Predict-then-Optimize Framework
Vishal Gupta, USC Marshall School Of Business -
Decoupling Learning and Decision-Making: Breaking the $O(\sqrt{T})$ Barrier in Online Resource Allocation with First-Order Methods
Chunlin Sun, Stanford University -
Optimizer's Information Criterion: Dissecting and Removing Bias in Data-Driven Optimization
Tianyu Wang, Columbia University
Stream 4b: Transportation and logistics
ThB155 — Models and Algorithms in Last-mile Delivery
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EV delivery, charging and parking planning method under uncertain arrival times at logistic depots
Hang Dong, Hitachi, Ltd. -
Optimizing Ultra-Fast Delivery Networks and Service Guarantees Under Uncertainty
Xin Wang, HEC Montréal -
Technician Routing and Scheduling under Uncertrainty
Milad Elyasi, Postdoctoral Research Fellow -
A contextual framework for learning routing experiences in last-mile delivery
Okan Arslan, HEC Montréal
ThB950 — Transportation and logistics 6
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An integer optimization approach for the graph-free multi-agent pathfinding problem
Seyoung Oh, Seoul National University -
Optimizing Containerized Multimodal Transport toward Sustainability and resilience
Asefeh Hassani Goodarzi, Département De Génie Des Systems, école De Technologie Supérieure -
Charging Station Location and Fleet Sizing for Shared Autonomous Electric Vehicles using Benders' Decomposition
Michael Levin, University of Minnesota -
Optimizing the Trade-Off Between Batching and Waiting: Subadditive Dispatching
Alejandro Toriello, Georgia Institute of Technology
Stream 4d: Energy and Environment
ThB118 — Optimization of Gas Networks
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Adjustable Robust Nonlinear Network Design under Demand Uncertainties
Julia Grübel, University of Technology Nuremberg (Utn) -
Mixture of Gases on Networks
Pascal Börner, Tu Darmstadt -
A tailored interior point method for fast optimization on gas networks
Rowan Turner, University of Edinburgh And Heriot Watt University -
Optimization methods for the analysis of gas markets
Lars Schewe, University of Edinburgh
ThB33 — Learning from Optimization in Energy
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On the Coupling Between Charging Scheduling of Electrified Bus Fleets and Grid Pricing
Nathan Cho, Cornell University -
Advancing Renewable Energy Simulation: Integrating Time Variant Hidden Markov Models with SDDP for Enhanced Accuracy and Real-World Application
Andre Felipe De Carvalho Ramos, PUC Rio -
Task-Based Prescriptive Trees for Two-Stage Linear Decision-Making Problems: Reformulations, Heuristic Strategies, and Applications
Bruno Fanzeres, PUC Rio -
Contextually Robust Optimization: End-to-End Learning in Power System Applications
Davi Valladão, Lamps Puc Rio
Stream 4i: Industrial applications
ThB963 — Industrial applications 1
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Faster Infeasibility Analysis for Linear Programs
John Chinneck, Systems And Computer Eng., Carleton University -
Novel Branch & Bound Tree Management for Fast Convergence of MIPs on Parallel Computers
Vijay Hanagandi, Optimal Solutions Inc -
Joint Transshipment, Markdown, and Clearance Decisions at a Fast-Fashion Retailer
Siamak Naderi, Teaching Fellow -
Optimizing Ticket Pricing with ExPretio's AI
Thibault Barbier, Expretio Technologies Inc.