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Stream 1a: Nonlinear Programming I
FA94 — Nonconvex optimization: landscapes and dynamics II
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** CANCELLED ** Deep Learning with Nontrivial Constraints
Ju Sun, University of Minnesota -
Adaptive Quasi-Newton and Anderson Acceleration with Global (Accelerated) Convergence Rates
Damien Scieur, Samsung Sail Montreal -
Non-Convexity Two Ways: new bounds for the Paulsen Problem via Geodesic PL-condition
Akshay Ramachandran, CWI And University of Amsterdam -
Strict saddle avoidance for Riemannian Gradient Descent
Andreea Musat, EPFL
FA260 — Open-source software for nonlinear programming
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Graph-Based Modeling and Optimization: Algorithms, Properties, and Software
David Cole, University of Wisconsin Madison -
Uno, a next-gen solver for unifying nonlinearly constrained nonconvex optimization
Charlie Vanaret, Argonne National Lab Zib -
Accelerating Optimal Power Flow with GPUs: SIMD Abstraction of Nonlinear Programs and Condensed-Space Interior-Point Methods
Mihai Anitescu, Argonne National Laboratory -
A Funnel SQP and Feasibility Solver for Direct Optimal Control within the acados Software Framework
David Kiessling, KU Leuven
FA83 — Gradient-based methods: theory and advances
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Nonconvex Stochastic Bregman Proximal Gradient Method with Application to Deep Learning
Jingyang Li, National University of Singapore -
Approximate Bregman Proximal Gradient Algorithm for Relatively Smooth Nonconvex Optimization
Shota Takahashi, The University of Tokyo -
Bregman Proximal Methods for Quantum Information Theoretic Problems
Kerry He, Monash University
Stream 1b: Global Optimization
FA27 — Global Optimal Search: Unleashing Maximum Potential
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Computing the conjugate of nonconvex bivariate piecewise linear-quadratic functions.
Tanmaya Karmarkar, UBC -
Norm-induced Non-Convex Relaxations for Lipschitz Constraints
Adrian Göß, University of Technology Nuremberg (Utn) -
On the impact of reliable boundary calculations by convex relaxation in global optimization
Frederic Messine, Laplace University of Toulouse -
Advances in convex relaxation generation for dynamic global optimization
Kamil Kamil Khan, Mcmaster University
Stream 1c: Nonsmooth Optimization
FA25 — Some recent advances in zeroth and first-order optimization methods
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Structure Utilization for Reducing Dimensional Dependency for Nonsmooth Derivative-Free Optimization
Ching Pei Lee, Institute of Statistical Mathematics -
Adaptable proximal algorithms: improved stepsize bounds and weaker assumptions
Andreas Themelis, Kyushu University -
MGProx: A nonsmooth multigrid proximal gradient method with adaptive restriction for strongly convex optimization
Andersen (Man Shun) Ang, University of Southampton -
Understanding Neural Network Binarization with Forward and Backward Proximal Quantizers
Yaoliang Yu, University of Waterloo
FA113 — Advances in Variational Analysis and Nonsmooth Optimization II
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An asynchronous parallel bundle method
Frank Fischer, Johannes Gutenberg University Mainz -
Geometric characterizations of Lipschitz stability for convex optimization problems
Nghia Tran, Oakland University -
First-Order Methods for Constrained Optimization Problems Under Distributional Uncertainties: Empirical Evaluations and Theory
Meisam Razaviyayn, University of Southern California -
Proximal Algorithms for Gaussian variational inference via JKO in the Bures-Wasserstein Space
Krishnakumar Balasubramanian, University of California, Davis
Stream 1d: Semi-Definite Programming
FA17 — Recent advances in conic optimization - Part 2
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** Permuted with Nosaka's talk in MB29 ** General Spectral Constrained Matrix Optimization
Casey Garner, University of Minnesota -
Non-facial Exposedness of Copositive Cones over Symmetric Cones
Mitsuhiro Nishijima, Tokyo Institute of Technology / The Institute of Statistical Mathematics -
Efficient Quantum Relative Entropy Programming with SDP Preprocessing
Mehdi Karimi, Illinois State University -
Convergence rate analysis of a Dykstra-type projection algorithm
Xiaozhou Wang, The Hong Kong Polytechnic University
FA89 — Recent advances in quadratic and semidefinite optimization
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Rounding semidefinite relaxations of concave functions of quadratic forms
Chenyang Yuan, Toyota Research Institute -
Complexity of Chordal Conversion for Sparse Semidefinite Programs with Small Treewidth
Richard Zhang, University of Illinois At Urbana Champaign -
A Semidefinite Hierarchy for Expected Independence Numbers of Random Graphs
Kevin Shu, Georgia Institute of Technology
Stream 1e: Variational Analysis, Variational Inequalities and Complementarity
FA103 — Recent advances in bilevel optimization
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Moreau envelope based reformulation and algorithm for bilevel programs
Shangzhi Zeng, University of Victoria -
On first-order methods for stochastic bilevel optimization
Jeongyeol Kwon, University of Wisconsin Madison -
Relaxation methods for pessimistic bilevel optimization
Alain Zemkoho, The University of Southampton -
Theoretical smoothing frameworks for general nonsmooth bilevel problems
Jan Harold Alcantara, Riken Center For Advanced Intelligence Project
Stream 1f: Random Methods for Continuous Optimization
FA51 — Splitting and Randomized Methods 3
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Optimal and approximate optimal parameters of the SOR-like iteration method for solving absolute value equations
Cairong Chen, Fujian Normal University -
A regularized splitting method for sums of multi-block maximal monotone operators and its relationship with symmetric ADMM
Xingju Cai, Nanjing Normal University -
** MOVED TO FRIDAY AM REMOTE SESSION ** Extended alternating structure-adapted proximal gradient algorithm for multiblock nonconvex optimization
Chunfeng Cui, Beihang University
Stream 1g: Derivative-free and Simulation-based Optimization
FA326 — DFO based on Approximations to Derivatives 2
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Black-Box Optimization Algorithms for Problems with Convex Regularizers
Yanjun Liu, Princeton University -
Zeroth-order low-rank Hessian estimation via matrix recovery
Tianyu Wang, Fudan University -
** MOVED TO FRIDAY AM REMOTE SESSION ** Derivative-free implementation of the regularized Newton method with lazy approximated Hessians
Geovani Grapiglia, Uclouvain -
On the connection between affine-invariance, convergence and learning second order information
Anne Auger, INRIA And Ecole Polytechnique
Stream 2a: Mixed Integer Linear Programming
FA228 — Integer programming: structure and algorithms
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Parameterized Algorithms for Block-Structured Integer Programs with Large Entries
Alexandra Anna Lassota, Eindhoven University of Technology -
Exploring Pure Nash Equilibria in Integer Programming Games for Aquatic Invasive Species Prevention
Hyunwoo Lee, Virginia Tech -
Total Matching and Subdeterminants
Luca Ferrarini, école Des Ponts Paristech -
Integer programs with nearly totally unimodular matrices: the cographic case
Stefan Kober, Université Libre De Bruxelles
FA262 — Aspects of Symmetry and Fairness in Integer Programming and Combinatorial Optimization
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FPT Algorithms using Minimal Parameters for a Generalized Version of Maximin Shares
Adrian Vetta, Mcgill University -
Handling symmetries in stable set problems and perfect mixed graphs
Annika Jaeger, Tu Darmstadt -
Fair Schedules for Single Round Robin Tournaments with Ranked Participants
Sten Wessel, Eindhoven University of Technology -
Detecting and Handling Reflection Symmetries in MINLP
Christopher Hojny, Tu Eindhoven
Stream 2b: Mixed Integer Nonlinear Programming
FA348 — Convexification Techniques for MINLP
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Exact Augmented Lagrangian Duality for Mixed Integer Convex Optimization
Abhishek Pathapati Pathapati, Indian Institute of Technology, Bombay -
Using quadratic cuts to iteratively strengthen convexifications of box quadratic programs
Amélie Lambert, Cedric CNAM -
The if-then Polytope: Conditional Relations over Multiple Sets of Binary Variables
Tobias Kuen, Fraunhofer IIS -
Cutting planes for multilinear optimization
Matthias Walter, University of Twente
Stream 2d: Machine Learning and Discrete Optimization
FA173 — Online talks in room 210CG with zoom link 933 0594 8837
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Remote talks
To Be Announced , GERAD -
Remote talks
To Be Announced , GERAD -
Remote talks
To Be Announced , GERAD -
Remote talks
To Be Announced , GERAD
Stream 2c: Combinatorial Optimization and Graph Theory
FA351 — Combinatorial Optimisation and Graph Theory
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Rounding the Lovasz Theta Function with a Value Function Approximation
Rui Gong, Georgia Institute of Technology -
Mixed-Integer Linear Optimization via Learning-Based Two-Layer Large Neighborhood Search
Akang Wang, Shenzhen Research Institute of Big Data -
Optimizing Mediated Graphs: Applications in Conic Optimization and Representations of Circuits as Sums-Of-Squares
Víctor Blanco, Universidad De Granada -
Packing cycles in planar and bounded-genus graphs
Niklas Schlomberg, University of Bonn
FA925 — Combinatorial Optimization and Graph Theory 5
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Labeling Methods for Partially Ordered Paths
Ricardo Euler, Zuse Institute Berlin -
Measuring Constituency Based On Minimum Campaign Distance And Application To Evaluate The Merger Of Electoral Districts
Yuichiro Miyamoto, Sophia University -
Combinatorial solving with provably correct results
Jakob Nordström, University Copenhagen -
On the monotonicity in steepest descent algorithm for M-convex functions
Akiyoshi Shioura, Tokyo Institute of Technology
Stream 2e: Approximation and Online Algorithms
FA245 — TSP and vehicle routing
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Improved guarantees for the a priori TSP
Luise Puhlmann, Research Institute For Discrete Mathematics, University of Bonn -
The k-Opt algorithm for the Traveling Salesman Problem has exponential running time for $k \geq 5$
Stefan Hougardy, University of Bonn -
Anytime Optimization Approaches for Online dial-a-ride problem
Elahe Amiri, Polytechnique Montréal -
Vehicle Routing with Time-Dependent Travel Times: Theory, Practice, and Benchmarks
Dirk Müller, University of Bonn
FA150 — Submodularity and Beyond in Approximation Algorithms
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Improved Approximation Algorithms Beyond Uncrossable Functions
Ishan Bansal, Cornell University -
Polyhedral Aspects of Feedback Vertex Set and Pseudoforest Deletion Set
Shubhang Kulkarni, University of Illinois At Urbana Champaign -
Quotient sparsification for submodular functions
Kent Quanrud, Purdue University -
Maximizing a Monotone Submodular Function Under an Unknown Knapsack Capacity
Sabine Münch, Trier University
Stream 2f: Computational Discrete and Integer Optimization
FA224 — Tightening MILPs by Reformulation
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Augmented subproblem grinding for the lot-type design problem
Jörg Rambau, University of Bayreuth -
An acceleration scheme for column generation in production-maintenance scheduling problems
João Dionísio, Cmup/Fcup -
A new approach for inter-sample avoidance using an integer polytope formulation
Johannes Schmidt, Brandenburg University of Technology Cottbus Senftenberg -
Dynamic Demand Propagation in Guaranteed Service Models
Dominik Kamp, University of Bayreuth, Chair Of Economathematics
FA933 — Computational Discrete and Integer Optimization 2
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Column Elimination
Anthony Karahalios, Carnegie Mellon University -
Sequential Mixed-Integer Programming for Matrix Sparsification
Andreas Tillmann, Tu Braunschweig -
An improved weighting local search for large-scale binary integer programs
Shunji Umetani, Recruit Co., Ltd. -
Sensitivity analysis for linear change of the constraint matrix of an LP
Quentin Louveaux, University of Liège
Stream 3a: Continuous Stochastic Programming
FA247 — Latest Developments in Stochastic Optimization
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Reinforcement Learning for Portfolio Optimization in Model with Regime-Switching
David Saunders, University of Waterloo -
Optimal trade execution with learning
Andrew Lim, National University of Singapore -
On Generalization and Regularization via Wasserstein Distributionally Robust Optimization
Qinyu Wu, University of Waterloo -
Model Aggregation for Risk Evaluation and Robust Optimization
Tiantian Mao, University of Science And Technology Of China
Stream 3c: Robust and Distributionally Robust Optimization
FA133 — Robust Optimization meets other domains
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Robust Appointment Scheduling with General Convex Uncertainty Sets
Judith Brugman, Tilburg University -
Connections and Reformulations between Robust and Bilevel Optimization
Johannes Thürauf, University Trier -
LP-based approximations for disjoint bilinear and two-stage adjustable robust optimization.
Ayoub Foussoul, Columbia University -
Quadratic Optimization Through the Lens of Adjustable Robust Optimization
Ahmadreza Marandi, Eindhoven University of Technology
FA140 — Robust Optimization for Operations Problems
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Robust topology optimization using the Bernstein approximation
Miguel Carrasco, Universidad De Los Andes -
Optimized Dimensionality Reduction for Moment-based Distributionally Robust Optimization
Kai Pan, The Hong Kong Polytechnic University -
Robust Workforce Management with Crowdsourced Delivery
Chun Cheng, Dalian University of Technology -
Robust Capacity Planning with General Upgrading
Zhenyu Hu, National University of Singapore
Stream 3d: Multi-stage Stochastic Programming and Reinforcement learning
FA182 — Advances at the intersection of reinforcement learning and stochastic optimization
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A Recurrent Reinforcement Learning Strategy for Online Scheduling of a State Task Network Under Uncertainty
Daniel Rangel Martinez, University of Waterloo -
A Unified Framework for Sequential Decision Problems: From Dynamic Programming/RL to Stochastic Programming
Warren Powell, Princeton University/Optimal Dynamics -
Inducing Group Fairness in Real-World Pipelines through Uncertainty Protections
Swati Gupta, MIT -
A Functional Model Method for Nonconvex Nonsmooth Conditional Stochastic Optimization
Andrzej Ruszczynski, Rutgers University
Stream 3e: Data-driven optimization
FA259 — New models and applications of data-driven optimization
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Robust Portfolio Optimization Meets Arbitrage Pricing Theory
Mateus Waga, PUC Rio -
Data-Driven Robust Sequential Search
Cagin Uru, Duke University -
Missing data in data-driven optimization
Hoda Bidkhori, George Mason University -
Pivotal Sampling for Online Bayesian Matching
Tristan Pollner, Stanford University
FA234 — Data-driven decision making in high-stakes domains: notes on fairness and interpretability
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Is There an Accuracy-Simplicity Tradeoff in High-Stakes Decision Domains?
Lesia Semenova, Duke University -
Learning Interpretable and Fair Housing Allocation Policy for Individuals Experiencing Homelessness in Los Angeles
Sina Aghaei, University of Southern California -
The Measure and Mismeasure of Fairness
Johann Gaebler, Harvard -
f-FERM: Robust and Fair Empirical Risk Minimization via f-divergences
Sina Baharlouei, University of Southern California
Stream 4b: Transportation and logistics
FA193 — Network Design for Transportation Planning IV
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Stochastic Variable Cost and Size Bin Packing with Capacity Loss and Supplier Selection problem
Guido Perboli, Politecnico Di Torino -
Continuous-Time Service Network Design with Stochastic Travel Times
Giacomo Lanza, University of Pisa -
Door-to-Door Multimodal Long-Distance Freight Transportation Planning
Mahdi Mostajabdaveh, Polytechnique Montréal -
Scheduled Service Network Design with Packing Considerations
Maria Elena Bruni, University of Calabria
Stream 4c: Scheduling and manufacturing
FA955 — Scheduling and manufacturing 4
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Daily production scheduling method for mixed-model assembly line and different workload models
Tazu Nomoto, Hitachi, Ltd. -
Flexible job shop scheduling problem with sequencing flexibility: constructive heuristics and local searches considering position-based learning effect
Debora Pretti Ronconi, University of São Paulo Production Engineering Department -
Solving an integrated lot sizing and preventive maintenance planning for a single machine
Harcènage Dansou, ESG UQAM -
Data Mining-Driven Shift Enumeration for Accelerating the Solution of Large-Scale Personnel Scheduling Problems
Farin Rastgar Amini, Polytechnique Montreal
Stream 4h: Game Theory
FA330 — Computing Equilibria of Games
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Learning in Multi-Leader Single-Follower Stackelberg Games
Francesco Morri, INRIA Lille -
Nash Equilibrium of Code-Share Mechanism under Airline Frequency Competition Game with Second Order Cone Programming
Zi Yi Huang, National Tsing Hua University -
Computing Quasi-Proper Equilibria: From a Characterization to a Differentiable Path-Following Method
Chuangyin Dang, City University of Hong Kong -
Tight Bounds for the Price of Fairness
Yichuan Ding, Desautels Faculty Of Management, Mcgill University
Stream 4i: Industrial applications
FA288 — Optimization and Validation of Execution Models at Amazon Scale
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Ideal inventory placement with demand spillover
Zihao Li, Amazon.Com -
Validating Network Planning via Customer Centric Baselines
Qi Chen, Amazon -
Dynamic Resource Allocation: Algorithmic Design Principles and Spectrum of Achievable Performances
Akshit Kumar, Columbia University, Graduate School Of Business -
Solving Large Scale Linear Problems with Lagrangian Decomposition
Ozlem Bilginer, Amazon.Com