Cover Image

Differentiable Integer Linear Programming is not Differentiable & it's not a mere technical problem

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	Sornwanee, Thanawat
Format:	Preprint
Published:	2026
Subjects:	Optimization and Control Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Unbiased Single-Queried Gradient for Combinatorial Objective
by: Sornwanee, Thanawat
Published: (2026)

Predicting Accurate Lagrangian Multipliers for Mixed Integer Linear Programs
by: Demelas, Francesco, et al.
Published: (2023)

Machine Learning Augmented Branch and Bound for Mixed Integer Linear Programming
by: Scavuzzo, Lara, et al.
Published: (2024)

Differentiation Through Black-Box Quadratic Programming Solvers
by: Magoon, Connor W., et al.
Published: (2024)

Learning Backdoors for Mixed Integer Linear Programs with Contrastive Learning
by: Cai, Junyang, et al.
Published: (2024)

Multi-task Representation Learning for Mixed Integer Linear Programming
by: Cai, Junyang, et al.
Published: (2024)

Mixed-Integer Programming for Change-point Detection
by: Narula, Apoorva, et al.
Published: (2026)

Learning Cut Generating Functions for Integer Programming
by: Cheng, Hongyu, et al.
Published: (2024)

Learning to Optimize by Differentiable Programming
by: Tao, Liping, et al.
Published: (2026)

A Distance Metric for Mixed Integer Programming Instances
by: Maudet, Gwen, et al.
Published: (2025)

On Integer Programming for the Binarized Neural Network Verification Problem
by: Kim, Woojin, et al.
Published: (2025)

Accelerated Nonnegative Tensor Completion via Integer Programming
by: Pan, Wenhao, et al.
Published: (2022)

A Penalty Approach for Differentiation Through Black-Box Quadratic Programming Solvers
by: Linghu, Yuxuan, et al.
Published: (2026)

Generalization Guarantees for Learning Branch-and-Cut Policies in Integer Programming
by: Cheng, Hongyu, et al.
Published: (2025)

Speeding Up Mixed-Integer Programming Solvers with Sparse Learning for Branching
by: Bayramoğlu, Selin, et al.
Published: (2026)

Effective Generation of Feasible Solutions for Integer Programming via Guided Diffusion
by: Zeng, Hao, et al.
Published: (2024)

Learning to Optimize for Mixed-Integer Non-linear Programming with Feasibility Guarantees
by: Tang, Bo, et al.
Published: (2024)

Expressive Power of Graph Neural Networks for (Mixed-Integer) Quadratic Programs
by: Chen, Ziang, et al.
Published: (2024)

Learning to Remove Cuts in Integer Linear Programming
by: Puigdemont, Pol, et al.
Published: (2024)

The Differentiable Feasibility Pump
by: Cacciola, Matteo, et al.
Published: (2024)

Towards An Unsupervised Learning Scheme for Efficiently Solving Parameterized Mixed-Integer Programs
by: Qu, Shiyuan, et al.
Published: (2024)

Solving 0-1 Integer Programs with Unknown Knapsack Constraints Using Membership Oracles
by: Messana, Rosario, et al.
Published: (2024)

Differentially Private Optimization with Sparse Gradients
by: Ghazi, Badih, et al.
Published: (2024)

Online Linear Programming with Batching
by: Xu, Haoran, et al.
Published: (2024)

A Unified Approach to Extract Interpretable Rules from Tree Ensembles via Integer Programming
by: Bonasera, Lorenzo, et al.
Published: (2024)

Differentiable Model Predictive Control on the GPU
by: Adabag, Emre, et al.
Published: (2025)

Feed-Forward Neural Networks as a Mixed-Integer Program
by: Aftabi, Navid, et al.
Published: (2024)

Communication-Efficient Distributed Learning with Differential Privacy
by: Ren, Xiaoxing, et al.
Published: (2026)

A General and Streamlined Differentiable Optimization Framework
by: Rosemberg, Andrew W., et al.
Published: (2025)

Accelerating Optimization via Differentiable Stopping Time
by: Xie, Zhonglin, et al.
Published: (2025)

Taming Binarized Neural Networks and Mixed-Integer Programs
by: Aspman, Johannes, et al.
Published: (2023)

Quadratic Objective Perturbation: Curvature-Based Differential Privacy
by: Cortild, Daniel, et al.
Published: (2026)

Automatic Differentiation of Optimization Algorithms with Time-Varying Updates
by: Mehmood, Sheheryar, et al.
Published: (2024)

Implicit Differentiation for Hyperparameter Tuning the Weighted Graphical Lasso
by: Pouliquen, Can, et al.
Published: (2023)

Nonsmooth Implicit Differentiation: Deterministic and Stochastic Convergence Rates
by: Grazzi, Riccardo, et al.
Published: (2024)

Nearly Optimal Linear Convergence of Stochastic Primal-Dual Methods for Linear Programming
by: Lu, Haihao, et al.
Published: (2021)

Differentiable Discrete Event Simulation for Queuing Network Control
by: Che, Ethan, et al.
Published: (2024)

Learning to Solve Optimization Problems Constrained with Partial Differential Equations
by: Guven, Yusuf, et al.
Published: (2025)

Differentiable Convex Optimization Layers in Neural Architectures: Foundations and Perspectives
by: Katyal, Calder
Published: (2024)

A Hessian-Aware Stochastic Differential Equation for Modelling SGD
by: Li, Xiang, et al.
Published: (2024)