Cover Image

Feature Augmentation of GNNs for ILPs: Local Uniqueness Suffices

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Han, Qingyu, Li, Qian, Yang, Linxin, Chen, Qian, Shi, Qingjiang, Sun, Ruoyu
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Optimization and Control
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

When GNNs meet symmetry in ILPs: an orbit-based feature augmentation approach
by: Chen, Qian, et al.
Published: (2025)

PDHG-Unrolled Learning-to-Optimize Method for Large-Scale Linear Programming
by: Li, Bingheng, et al.
Published: (2024)

An Efficient Unsupervised Framework for Convex Quadratic Programs via Deep Unrolling
by: Yang, Linxin, et al.
Published: (2024)

Enhancing GNNs Performance on Combinatorial Optimization by Recurrent Feature Update
by: Pugacheva, Daria, et al.
Published: (2024)

SymILO: A Symmetry-Aware Learning Framework for Integer Linear Optimization
by: Chen, Qian, et al.
Published: (2024)

On Representing Convex Quadratically Constrained Quadratic Programs via Graph Neural Networks
by: Wu, Chenyang, et al.
Published: (2024)

Adam Converges Without Any Modification On Update Rules
by: Zhang, Yushun, et al.
Published: (2026)

Optimal Depth of Neural Networks
by: Qi, Qian
Published: (2025)

Towards Quantifying the Hessian Structure of Neural Networks
by: Dong, Zhaorui, et al.
Published: (2025)

State estimations and noise identifications with intermittent corrupted observations via Bayesian variational inference
by: Sun, Peng, et al.
Published: (2026)

A Single-Loop Smoothed Gradient Descent-Ascent Algorithm for Nonconvex-Concave Min-Max Problems
by: Zhang, Jiawei, et al.
Published: (2020)

Accelerating Single-Pass SGD for Generalized Linear Prediction
by: Chen, Qian, et al.
Published: (2026)

On the Convergence of Adam under Non-uniform Smoothness: Separability from SGDM and Beyond
by: Wang, Bohan, et al.
Published: (2024)

Locally Regularized Sparse Graph by Fast Proximal Gradient Descent
by: Sun, Dongfang, et al.
Published: (2024)

Learning Provably Improves the Convergence of Gradient Descent
by: Song, Qingyu, et al.
Published: (2025)

Solving Max-Cut to Global Optimality via Feasibility-Preserving Graph Neural Networks
by: Chen, Hao, et al.
Published: (2026)

The Effectiveness of Local Updates for Decentralized Learning under Data Heterogeneity
by: Wu, Tongle, et al.
Published: (2024)

Learning-Augmented Decentralized Online Convex Optimization in Networks
by: Li, Pengfei, et al.
Published: (2023)

Local Linear Convergence of Infeasible Optimization with Orthogonal Constraints
by: Sun, Youbang, et al.
Published: (2024)

Towards Robust Learning to Optimize with Theoretical Guarantees
by: Song, Qingyu, et al.
Published: (2025)

Accelerating Decentralized Optimization via Overlapping Local Steps
by: Zhou, Yijie, et al.
Published: (2026)

On the Mechanism and Dynamics of Modular Addition: Fourier Features, Lottery Ticket, and Grokking
by: He, Jianliang, et al.
Published: (2026)

Bregman Linearized Augmented Lagrangian Method for Nonconvex Constrained Stochastic Zeroth-order Optimization
by: Shi, Qiankun, et al.
Published: (2025)

Robust Control with Gradient Uncertainty
by: Qi, Qian
Published: (2025)

Universal Approximation Theorem for Deep Q-Learning via FBSDE System
by: Qi, Qian
Published: (2025)

Enhancing Unsupervised Feature Selection via Double Sparsity Constrained Optimization
by: Xiu, Xianchao, et al.
Published: (2025)

Communication-Efficient Adaptive Batch Size Strategies for Distributed Local Gradient Methods
by: Lau, Tim Tsz-Kit, et al.
Published: (2024)

Mean-Field Control on Sparse Graphs: From Local Limits to GNNs via Neighborhood Distributions
by: Schmidt, Tobias, et al.
Published: (2026)

Muon is Provably Faster with Momentum Variance Reduction
by: Qian, Xun, et al.
Published: (2025)

Almost Sure Convergence Rates and Concentration of Stochastic Approximation and Reinforcement Learning with Markovian Noise
by: Qian, Xiaochi, et al.
Published: (2024)

Subsampled Ensemble Can Improve Generalization Tail Exponentially
by: Qian, Huajie, et al.
Published: (2024)

Provable Adaptivity of Adam under Non-uniform Smoothness
by: Wang, Bohan, et al.
Published: (2022)

Efficient Group Lasso Regularized Rank Regression with Data-Driven Parameter Determination
by: Lin, Meixia, et al.
Published: (2025)

AdaSwitch: An Adaptive Switching Meta-Algorithm for Learning-Augmented Bounded-Influence Problems
by: Chen, Xi, et al.
Published: (2025)

Which Features are Best for Successor Features?
by: Ollivier, Yann
Published: (2025)

Principled Penalty-based Methods for Bilevel Reinforcement Learning and RLHF
by: Shen, Han, et al.
Published: (2024)

Local adapt-then-combine algorithms for distributed nonsmooth optimization: Achieving provable communication acceleration
by: Guo, Luyao, et al.
Published: (2026)

Local LMO: Constrained Gradient Optimization via a Local Linear Minimization Oracle
by: Richtárik, Peter, et al.
Published: (2026)

A Theory of Feature Learning in Kernel Models
by: Chen, Yunlu, et al.
Published: (2023)

Shallow Neural Networks Learn Low-Degree Spherical Polynomials with Feature Learning by Learnable Channel Attention
by: Yang, Yingzhen
Published: (2025)