Imagen de Portada

The Geometry of Linear Program Compression: An Exact Characterization and Learning Algorithm

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Ye, Yuhan, Bennouna, Omar
Formato:	Preprint
Publicado:	2026
Materias:	Optimization and Control 90C05 (Primary), 90C60, 68Q32, 90C31, 52B55 (Secondary)
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Learning Decision-Sufficient Representations for Linear Optimization
por: Ye, Yuhan, et al.
Publicado: (2026)

On Tail Decay and Moment Estimates of a Condition Number for Random Linear Conic Systems
por: Cheung, Dennis, et al.
Publicado: (2003)

Parameterized Complexity of Stationarity Testing for Piecewise-Affine Functions and Shallow CNN Losses
por: Ye, Yuhan
Publicado: (2026)

Online Convex Optimization Using Coordinate Descent Algorithms
por: Lin, Yankai, et al.
Publicado: (2022)

Solving Regularized Multifacility Location Problems with Unknown Number of Centers via Difference-of-Convex Optimization
por: Geremew, W., et al.
Publicado: (2026)

Efficient Learning for Entropy-Regularized Markov Decision Processes via Multilevel Monte Carlo
por: Meunier, Matthieu, et al.
Publicado: (2025)

On the Curvature of the Central Path of Linear Programming Theory
por: Dedieu, Jean-Pierre, et al.
Publicado: (2003)

On the Hardness of Short and Sign-Compatible Circuit Walks
por: Borgwardt, Steffen, et al.
Publicado: (2024)

Exact Solution to Data-Driven Inverse Optimization of MILPs in Finite Time via Gradient-Based Methods
por: Kitaoka, Akira
Publicado: (2024)

Efficiency and Convergence Insights in Large-Scale Optimization Using the Improved Inexact-Newton-Smart Algorithm and Interior-Point Framework
por: Renani, Neda Bagheri, et al.
Publicado: (2025)

Exactness and Effective Degree Bound of Lasserre's Relaxation for Polynomial Optimization over Finite Variety
por: Hua, Zheng, et al.
Publicado: (2021)

The global convergence time of stochastic gradient descent in non-convex landscapes: Sharp estimates via large deviations
por: Azizian, Waïss, et al.
Publicado: (2025)

Continuity in Parametric Linear Programming
por: Lahiri, Somdeb
Publicado: (2024)

Zeroth-order Random Subspace Algorithm for Non-smooth Convex Optimization
por: Nozawa, Ryota, et al.
Publicado: (2024)

What is the long-run distribution of stochastic gradient descent? A large deviations analysis
por: Azizian, Waïss, et al.
Publicado: (2024)

Riemannian Adaptive Regularized Newton Methods with Hölder Continuous Hessians
por: Zhang, Chenyu, et al.
Publicado: (2023)

A sensitivity-based method for bilevel optimization problems: Theoretical analysis and computational performance
por: Nolasco, Eduardo, et al.
Publicado: (2025)

Optimistic Bilevel Optimization with Composite Lower-Level Problem
por: Solla, Mattia, et al.
Publicado: (2026)

Average-case thresholds for exact regularization of linear programs
por: Friedlander, Michael P., et al.
Publicado: (2025)

A Comparison of Models for Rolling Stock Scheduling
por: Grimm, Boris, et al.
Publicado: (2023)

On the Wasserstein alignment problem
por: Pal, Soumik, et al.
Publicado: (2025)

Second-order cone programming for distributionally robust compliance optimization of trusses considering input distribution uncertainty
por: Fujiyama, Takumi, et al.
Publicado: (2025)

Stratification for Nonlinear Semidefinite Programming
por: Bao, Chenglong, et al.
Publicado: (2026)

Automating Idealness Proofs for Binary Programs with Application to Rectangle Packing
por: Fravel, Jamie, et al.
Publicado: (2026)

Barrier Algorithms for Constrained Non-Convex Optimization
por: Dvurechensky, Pavel, et al.
Publicado: (2024)

Zeroes and Extrema of Functions via Random Measures
por: Micheas, Athanasios Christou
Publicado: (2025)

Concave Certificates: Geometric Framework for Distributionally Robust Risk and Complexity Analysis
por: Chu, Hong T. M.
Publicado: (2026)

Learning to Choose Branching Rules for Nonconvex MINLPs
por: Berthold, Timo, et al.
Publicado: (2026)

Predict-then-Calibrate: A New Perspective of Robust Contextual LP
por: Sun, Chunlin, et al.
Publicado: (2023)

An Inexact Feasible Interior Point Method for Linear Optimization with High Adaptability to Quantum Computers
por: Mohammadisiahroudi, Mohammadhossein, et al.
Publicado: (2023)

Developing heuristic solution techniques for large-scale unit commitment models
por: Kempke, Nils-Christian, et al.
Publicado: (2025)

Augmentation Algorithms for Integer Programs with Total Variation-like Regularization
por: Yang, Dominic, et al.
Publicado: (2025)

Sailing League Problems
por: Schüler, Robert, et al.
Publicado: (2022)

Blended Conditional Gradients: the unconditioning of conditional gradients
por: Braun, Gábor, et al.
Publicado: (2018)

The Non-Substitution Theorem, Uniqueness of Solution and Convex combinations of basic optimal solutions for linear optimization
por: Lahiri, Somdeb
Publicado: (2024)

Scaling limits of multi-period distributionally robust optimization problems
por: Nendel, Max, et al.
Publicado: (2025)

A Near-Optimal Total Complexity for the Inexact Accelerated Proximal Gradient Method via Quadratic Growth
por: Li, Hongda, et al.
Publicado: (2026)

Constraint Identification and Algorithm Stabilization for Degenerate Nonlinear Programs
por: Wright, Stephen J.
Publicado: (2000)

How a Small Amount of Data Sharing Benefits Distributed Optimization and Learning : The Upside of Data Heterogeneity
por: Zhu, Mingxi, et al.
Publicado: (2022)

Constraint Qualification for Generic Parameter Families of Constraints in Optimization
por: Hamada, Naoki, et al.
Publicado: (2025)