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Stream 1a: Nonlinear Programming I
TB67 — Numerical Optimization for Machine Learning 1
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Relative Monte Carlo for Reinforcement Learning
Audrey Bazerghi, Northwestern University -
Structured Inverse-free Matrix Adaptive Methods for Large Neural Networks
Wu Lin, Vector Institute -
Target-based Surrogates for Stochastic Optimization
Jonathan Lavington, Univeristy Of British Columbia -
Stochastic Extragradient Methods: New Convergence Guarantees for Monotone and Non-monotone Variational Inequalities
Nicolas Loizou, Johns Hopkins University
TB136 — First-order Methods and Large-scale Optimization I
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Activity Identification in Non-smooth Optimization: A Set-Valued Operator Perspective
Ziqi Qin, Shanghai Jiao Tong University -
Goldstein modulus in Lipschitz Minimization
Siyu Kong, Cornell University -
Convergence of heavy-ball SGD in the nonconvex case: a novel time window-based analysis
Bohao Ma, The Chinese University of Hong Kong, Shenzhen -
Error bounds, PL condition, and quadratic growth for weakly convex functions, and linear convergences of proximal point methods
Feng Yi Liao, University of California, San Diego, Electrical And Computer Engineering Department
TB69 — From First- to High-order Methodologies: Recent Advances and Trends II
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Tensor Methods for Nonconvex Optimization using Cubic-quartic regularization models
Kate Wenqi Zhu, University of Oxford -
A consistently adaptive trust-region method
Fadi Hamad, University of Pittsburgh -
A randomized algorithm for nonconvex minimization with inexact evaluations and complexity guarantees
Shuyao Li, University of Wisconsin Madison -
A MINRES-based Algorithm Framework for Unconstrained Nonconvex Optimization with Non-positive Curvature Detection
Hanfeng Zeng, The Chinese University of Hong Kong, Shenzhen
TB60 — Advances in numerical methods for large scale nonlinear optimization and applications III
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Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm
Wanping Dong, University of Michigan -
Solving large-scale nonlinear least-squares with random Gauss-Newton models
Stefania Bellavia, University of Florence -
A stochastic gradient method with variance control and variable learning rate for Deep Learning
Giorgia Franchini, Unimore -
Probabilistic Trust Region method for solving Multi-objective Problems
Luka Rutesic, University of Novi Sad, Faculty of Sciences
Stream 1b: Global Optimization
TB5 — Polynomial and Conic Optimization
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Strengthening convex relaxations of the radial optimal power flow problem via copositive optimization
Markus Gabl, Karlsruhe Institute of Technology -
Uncertain standard quadratic optimization under distributional assumptions: a chance-constrained epigraphic approach
Immanuel Bomze, University of Vienna -
SDPs for Moment Optimisation with Piecewise SOS-Convex Functions
Queenie Huang, University of New South Wales
Stream 1c: Nonsmooth Optimization
TB63 — Nonsmooth Stochastic Optimization and Applications
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High-dimensional Limit of Stochastic Optimization Methods with Structured Data
Inbar Seroussi, Tel-Aviv University -
Distributionally Robust Mean-Lower Partial Moment (LPM) Model and its Application in Portfolio Selection
Jie Jiang, Chongqing University -
Data-driven Distributionally Robust Multiproduct Pricing Problems under Pure Characteristics Demand
Hailin Sun, Nanjing Normal University
TB207 — Large scale continuous optimization and first-order methods and related topics
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Level-set geometry and the complexity of restarted PDHG for conic LP
Zikai Xiong, MIT Operations Research Center -
A Practical and Optimal First-Order Method for Large-Scale Convex Quadratic Programming
Haihao Lu, The University of Chicago -
A feasible method for solving general convex low-rank SDP problems
Tianyun Tang, National University of Singapore -
Practical Large-Scale Linear Programming using Primal-Dual Hybrid Gradient
David Applegate, Google Research
Stream 1d: Semi-Definite Programming
TB66 — SDP and Combinatorial Optimization
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Eigenvalue cuts for the Traveling Salesman Problem
Michael Smith, Lewis University/Northern Illinois University -
Computational study of rounded psd inequalities for the Max-Cut and k-cluster problem
Timotej Hrga, University of Klagenfurt -
Edge Expansion: Exploring SDP-Based Computational Strategies
Angelika Wiegele, University of Klagenfurt -
Facial Reduction of Semidefinite Relaxations of Binary Quadratic Problems
Ian Sugrue, Northern Illinois University
TB87 — Semidefinite Programming and Convex Algebraic Geometry
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Closing nonzero duality gaps by perturbation in SDP and its extension
Takashi Tsuchiya, National Graduate Institute For Policy Studies -
Any-dimensional learning
Eitan Levin, Caltech -
Polynomial Lower Approximation for Two-Stage Stochastic Optimization
Suhan Zhong, Texas A&M University -
Cubic interpolation to certify nonnegativity
Mitchell Harris, Massachusetts Institute of Technology
Stream 1e: Variational Analysis, Variational Inequalities and Complementarity
TB311 — New insights into first- and second-order variational analysis
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Quasidensity and certain classes of multifunctions
Stephen Simons, Uc Santa Barbara -
Kurdyka-Lojasiewicz exponent for a class of Hadamard-difference-parameterized models
Ting Kei Pong, Hong Kong Polytechnic University -
On second-order variational analysis of prox-regular functions
Helmut Gfrerer, Johannes Kepler University Linz -
Stability of nonsmooth optimization problems
Tim Hoheisel, Mcgill University
TB314 — Algorithms for optimization, monotone inclusions and variational inequalities 2
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** CANCELLED ** A projected semismooth Newton method for a class of nonconvex composite programs with strong prox-regularity
Jiayuan Wu, Peking University -
Accelerated gradient descent: A guaranteed bound for a heuristic restart strategy
Viktor Pavlovic, University of Waterloo -
Forward-Backward algorithms for weakly convex problems
Ewa Bednarczuk, Systems Research Institute, Polish Academy Of Sciences -
** CANCELLED ** Zeroth order and first order primal dual alternating proximal gradient algorithms for nonsmooth nonconvex minimax problems with coupled linear constraints
Zi Xu, Shanghai University
Stream 1f: Random Methods for Continuous Optimization
TB131 — Beyond Standard Assumptions in Optimization: Structured Non-Convexity, Non-Monotonicity, and Non-Smoothness
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Generalized-Smooth Nonconvex Optimization is As Efficient As Smooth Nonconvex Optimization
Yi Zhou, University of Utah -
Stochastic Optimization under Hidden Convexity
Ilyas Fatkhullin, ETH Zürich -
Convergence of Douglas--Rachford Splitting and Primal-Dual Hybrid Gradient for Non-Monotone, Non-Smooth Problems
Brecht Evens, KU Leuven -
On the Lower Bound of Minimizing Polyak-Lojasiewicz functions
Cong Fang, Peking University
Stream 1g: Derivative-free and Simulation-based Optimization
TB322 — Recent Progresses in DFO 1
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The cosine measure relative to a subspace
Gabriel Jarry Bolduc, Saint Francis Xavier University -
A (forgotten) subspace framework for large-scale derivative-free optimization
Zaikun Zhang, The Hong Kong Polytechnic University -
Parallel versions of the mesh adaptive direct search algorithm
Samuel Mendoza, Polytechnique Montréal -
Worst case complexity bounds for linesearch-type derivative-free algorithms
Giampaolo Liuzzi, Diag Sapienza University of Rome
Stream 1h: Optimal Control, PDE Constrained Optimization, and Multi-level Methods
TB91 — Nonsmooth PDE Constrained Optimization 3
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An Inexact Trust-Region Algorithm for Nonsmooth Risk-Averse Optimization
Drew Kouri, Sandia National Laboratories -
Control in the Coefficients of an Obstacle Problem
Nicolai Simon, Uni Hamburg -
A Discontinuous Galerkin Method for Optimal Control of the Obstacle Problem
Rohit Khandelwal, George Mason University -
Limiting Descent Directions in p-Harmonic Shape Optimization
Henrik Wyschka, Universität Hamburg
Stream 2a: Mixed Integer Linear Programming
TB915 — Mixed Integer Linear Programming 1
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A column generation approach for a challenging real-world routing problem
Nils Hassan Quttineh, Linköping University -
Complexity of Determining Unboundedness in Linear Bilevel Optimization
Bárbara Rodrigues, University of Edinburgh -
On the geometric and computational complexity of polynomial bilevel optimization
Quoc Tung Le, Toulouse School Of Economics
Stream 2b: Mixed Integer Nonlinear Programming
TB195 — Optimization over integers, cones and polynomials
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Spurious local minima in nonconvex sum-of-square optimization
Shixuan Zhang, Texas A&M University -
Solving Nonconvex Optimization Problems using Outer Approximations of the Set-Copositive Cone
Kurt Anstreicher, University of Iowa -
Integer Points in Arbitrary Convex Cones: The Case of the PSD and SOC Cones
Luze Xu, University of California, Davis -
On Polynomial-Time Solvability of Combinatorial Markov Random Fields
Shaoning Han, National University of Singapore
Stream 2c: Combinatorial Optimization and Graph Theory
TB86 — Spectral Graph Theory and Optimization
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Graphs with well-structured eigenbases
Hermie Monterde, University of Manitoba -
On the max k-cut and the eigenvalue of a graph
Leonardo Lima, Universidade Federal Do Paraná -
Main Signless Laplacian Eigenvalues of Quasi-Threshold Graphs
Cybele Vinagre, Universidade Federal Fluminense -
Zero forcing and eigenvalue multiplicities
Shahla Nasserasr, Rochester Institute of Technology
Stream 2d: Machine Learning and Discrete Optimization
TB199 — Learning to Select
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Minimizing difference of submodular functions via DC programming
George Orfanides, Mcgill University -
Slowly varying regression under sparsity
Vassilis Digalakis, HEC Paris -
Learning to Cover: Online Learning and Optimization with Irreversible Decisions
Michael Li, Harvard Business School -
Optimal Experimentation for Learning Personalized Policies Across Locations
Stefanos Poulidis, INSEAD
Stream 2f: Computational Discrete and Integer Optimization
TB340 — Solver Software II
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A modeling language-based approach to automatically recommend first-order optimization methods.
Sofiane Tanji, Uclouvain -
Symmetry detection in Mixed-Integer Conic Programming
Sven Wiese, Mosek APS -
Hybridizing combinatorial heuristics and continuous optimization methods for Mixed-Integer Programming
Julien Darlay, Hexaly -
Recent Advances in the SAS Linear and Mixed-integer Optimization Solvers
Philipp Christophel, Sas Institute Gmbh
Stream 3a: Continuous Stochastic Programming
TB111 — PDE-constrained optimization under uncertainty
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Optimality Conditions with Probabilistic State Constraints
Caroline Geiersbach, Weierstrass Institute For Applied Analysis And Stochastics -
Convergence rates for ensemble-based solutions to optimal control of uncertain dynamical systems
Johannes Milz, Georgia Institute of Technology -
Adaptive Surrogate Modeling for Trajectory Optimization with Model Inexactness
Matthias Heinkenschloss Matthias, Rice University -
Empirical estimators for risk-neutral composite optimal control with applications to bang-bang control
Daniel Walter, Humboldt Universität Zu Berlin
Stream 3b: Discrete Stochastic Programming
TB187 — Modeling and Algorithms for Stochastic Discrete Optimization
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Optimization via Simulation with Discontinuous Recourse Function
Zhuo Zhang, The Chinese University of Hong Kong, Shenzhen -
A Distributed Optimization Method for Large-Scale Production Planning Problem
Xingyu Lin, The Chinese University of Hong Kong, Shenzhen -
Risk-Aware Security-Constrained Unit Commitment
Cheng Guo, Clemson University -
Beyond Absolute Continuity: a New Class of Dynamic Risk Measures
Luhao Zhang, Columbia University
Stream 3c: Robust and Distributionally Robust Optimization
TB100 — Robust Optimization and Machine Learning 2
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Bayesian Risk-Averse Reinforcement Learning
Yuhao Wang, Georgia Institute of Technology -
Robust Regret Markov Decision Processes
Chin Pang Ho, City University of Hong Kong -
Distributionally Robust Path Integral Control
Duo Zhou, University of Illinois Urbana Champaign -
Towards Optimal Offline Reinforcement Learning
Mengmeng Li, EPFL
TB168 — Robust Optimization in practice
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Superior and Light Pareto Robust Optimization for IMRT Treatment Planning
Houra Mahmoudzadeh, University of Waterloo -
Dealing With Uncertainty Over Time When Optimizing Industrial Decarbonization Pathways
Justin Starreveld, University of Amsterdam -
A Holistic Framework for Decarbonization at OCP
Periklis Petridis, MIT -
Robust Facility Location in Disaster Preparation for Earthquakes with Aftershocks
Minakshi Punam Mandal, Essec Business School
Stream 3d: Multi-stage Stochastic Programming and Reinforcement learning
TB22 — Stochastic Dual Dynamic Programming : theory and applications
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Duality, upper bounds, and policy quality in Multistage Stochastic Programming
Bernardo Freitas Paulo Da Costa, Fundação Getúlio Vargas -
Data-Driven Stochastic Dual Dynamic Programming: Performance Guarantees and Regularization Schemes
Grani A Hanasusanto, University of Illinois Urbana Champaign -
Multistage stochastic inventory optimization with contracting
Andy Philpott, The University of Auckland -
A Multicut Approach to Compute Upper Bounds for Risk-Averse SDDP
Joaquim Dias Garcia, PSR
Stream 3e: Data-driven optimization
TB73 — Data-driven Methods for Contextual Stochastic Optimization
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Robust End-to-End Learning under Endogenous Uncertainty
Rares Cristian, Massachusetts Institute of Technology -
Robust Actionable Prescriptive Analytics
Minglong Zhou, Fudan University -
Integrated Conditional Estimation-Optimization
Meng Qi, Cornell University -
Conformal Contextual Optimization with a Smart Predict-then-Optimize Method
Paul Grigas, UC Berkeley
Stream 4b: Transportation and logistics
TB166 — Network Design for Transportation Planning I
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Benders Decomposition for Two-layer Network Design with Capacity Decisions
Ali Rouhani, Département D’informatique Et De Recherche Opérationnelle, Université De Montréal, Montreal, Qc, Canada -
From Tactical to Operational Planning: Implementation Policies for Consolidation-based Freight Transportation Systems
Saeedeh Dehghani, UQAM -
Service Network Design with Uncertainty on Water Levels for Intermodal River Transport
Bita Payami Shabestari, Phd Student -
Tactical Planning in Multi-Stakeholder Freight Transportation Systems under Uncertainty
Nadia Tahmasbi, CIRRELT And Université du Québec à Montréal
TB945 — Transportation and logistics 1
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A Comprehensive Stochastic Programming Model for Transfer Synchronization in Transit Networks
Zahra Ansarilari, University of Toronto Alumna -
Flexible and modular energy systems modelling with JuMP; A case study from the Arctic
Lars Hellemo, SINTEF -
Electric Vehicle Routing Problem with Robots, Parcel Lockers, and Time Windows
Nima Moradi, Information Systems Engineering, Concordia University -
Service level requirements in real-life-sized bike sharing systems
Jean François Côté, CIRRELT, Université Laval Québec, Canada
TB946 — Transportation and logistics 2
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Neural Network Estimators for Optimal Tour Lengths of Traveling Salesperson Problem Instances with Arbitrary Node Distributions
Taha Varol, HEC Montréal -
Online Stochastic Optimization for Real-Time Transfer Synchronization in Public Transportation Networks
Laura Kolcheva, Polytechnique Montréal -
Distributionally robust facility location problem under facility disruption, uncertain demand and cost
Shen Peng, Xidian University
Stream 4a: Networks and Telecom
TB943 — Networks and Telecom 1
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Budgeted spanning trees and polyhedra
Charles Nourry, Lamsade Université Paris Dauphine -
On Graphs with Finite-Time Consensus and Their Use in Gradient Tracking
Cesar A Uribe, Rice University
Stream 4d: Energy and Environment
TB292 — Optimization models for electric vehicle charging problems 2
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Improving Cloud Service Sustainability with Bilevel Optimization under Demand Uncertainty
Nathalia Wolf, INRIA -
The Electric Bus Rostering and Charging Scheduling Problem with Uncertain Energy Consumption: a Two-Stage Stochastic Programming Approach
Kyra Ann D’ignazio, HEC Montréal -
Integrated Location, Sizing and Pricing for Electric Vehicle Charging Stations
Miguel Anjos, University of Edinburgh
Stream 4c: Scheduling and manufacturing
TB952 — Scheduling and manufacturing 1
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Growing a stochastic subtree for mixed integer linear programming under uncertainty
Zoe Fornier, ENPC -
Stochastic optimization of bus schedules
Léa Ricard, EPFL -
Integrated lot sizing and blending problems under demand uncertainty
Maurício Gonçalves, UNESP Ibilce Exchange Phd Researcher At Hec Montréal