Cover Image

FrontierCO: Real-World and Large-Scale Evaluation of Machine Learning Solvers for Combinatorial Optimization

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Feng, Shengyu, Sun, Weiwei, Li, Shanda, Talwalkar, Ameet, Yang, Yiming
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

CoMind: Towards Community-Driven Agents for Machine Learning Engineering
by: Li, Sijie, et al.
Published: (2025)

Spend Less, Fit Better: Budget-Efficient Scaling Law Fitting via Active Experiment Selection
by: Li, Sijie, et al.
Published: (2026)

CodePDE: An Inference Framework for LLM-driven PDE Solver Generation
by: Li, Shanda, et al.
Published: (2025)

Unsupervised Diffusion Solver for Combinatorial Optimization via Combinatorial Adjoint Matching
by: Feng, Shengyu, et al.
Published: (2026)

CO-Bench: Benchmarking Language Model Agents in Algorithm Search for Combinatorial Optimization
by: Sun, Weiwei, et al.
Published: (2025)

Regularized Langevin Dynamics for Combinatorial Optimization
by: Feng, Shengyu, et al.
Published: (2025)

Sample Complexity and Representation Ability of Test-time Scaling Paradigms
by: Huang, Baihe, et al.
Published: (2025)

Learn Hard Problems During RL with Reference Guided Fine-tuning
by: Wu, Yangzhen, et al.
Published: (2026)

Learning to Relax: Setting Solver Parameters Across a Sequence of Linear System Instances
by: Khodak, Mikhail, et al.
Published: (2023)

UPS: Efficiently Building Foundation Models for PDE Solving via Cross-Modal Adaptation
by: Shen, Junhong, et al.
Published: (2024)

The Impact of Element Ordering on LM Agent Performance
by: Chi, Wayne, et al.
Published: (2024)

SORREL: Suboptimal-Demonstration-Guided Reinforcement Learning for Learning to Branch
by: Feng, Shengyu, et al.
Published: (2024)

SPL-LNS: Sampling-Enhanced Large Neighborhood Search for Solving Integer Linear Programs
by: Feng, Shengyu, et al.
Published: (2025)

Pre-Generating Multi-Difficulty PDE Data for Few-Shot Neural PDE Solvers
by: Choudhary, Naman, et al.
Published: (2025)

Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators
by: Li, Shanda, et al.
Published: (2025)

Agreement-Based Cascading for Efficient Inference
by: Kolawole, Steven, et al.
Published: (2024)

Provably tuning the ElasticNet across instances
by: Balcan, Maria-Florina, et al.
Published: (2022)

Understanding Optimization in Deep Learning with Central Flows
by: Cohen, Jeremy M., et al.
Published: (2024)

Multitask Learning Can Improve Worst-Group Outcomes
by: Kulkarni, Atharva, et al.
Published: (2023)

Where Does My Model Underperform? A Human Evaluation of Slice Discovery Algorithms
by: Johnson, Nari, et al.
Published: (2023)

Leader Reward for POMO-Based Neural Combinatorial Optimization
by: Wang, Chaoyang, et al.
Published: (2024)

Neural Solver Selection for Combinatorial Optimization
by: Gao, Chengrui, et al.
Published: (2024)

Learning to Optimize Package Picking for Large-Scale, Real-World Robot Induction
by: Li, Shuai, et al.
Published: (2025)

Transfer Learning for Deep-Unfolded Combinatorial Optimization Solver with Quantum Annealer
by: Hagiwara, Ryo, et al.
Published: (2025)

Efficient Training of Multi-task Neural Solver for Combinatorial Optimization
by: Wang, Chenguang, et al.
Published: (2023)

Differentiation of Blackbox Combinatorial Solvers
by: Vlastelica, Marin, et al.
Published: (2019)

WeCon: An Efficient Weight-Conditioned Neural Solver for Multi-Objective Combinatorial Optimization Problems
by: Wu, Xuan, et al.
Published: (2026)

Combinatorial Optimization Augmented Machine Learning
by: Schiffer, Maximilian, et al.
Published: (2026)

RRNCO: Towards Real-World Routing with Neural Combinatorial Optimization
by: Son, Jiwoo, et al.
Published: (2025)

Divide and Learn: Multi-Objective Combinatorial Optimization at Scale
by: Singh, Esha, et al.
Published: (2026)

CADO: From Imitation to Cost Minimization for Heatmap-based Solvers in Combinatorial Optimization
by: Song, Hyungseok, et al.
Published: (2026)

Everybody Prune Now: Structured Pruning of LLMs with only Forward Passes
by: Kolawole, Steven, et al.
Published: (2024)

Frontiers of Deep Learning: From Novel Application to Real-World Deployment
by: Xie, Rui
Published: (2024)

Enhancing Training Data Attribution with Representational Optimization
by: Sun, Weiwei, et al.
Published: (2025)

Active Hypothesis Testing for Correlated Combinatorial Anomaly Detection
by: Yang, Zichuan, et al.
Published: (2026)

xbench: Tracking Agents Productivity Scaling with Profession-Aligned Real-World Evaluations
by: Chen, Kaiyuan, et al.
Published: (2025)

Learning Personalized Decision Support Policies
by: Bhatt, Umang, et al.
Published: (2023)

Thinking vs. Doing: Agents that Reason by Scaling Test-Time Interaction
by: Shen, Junhong, et al.
Published: (2025)

Research on Effectiveness Evaluation and Optimization of Baseball Teaching Method Based on Machine Learning
by: Sun, Shaoxuan, et al.
Published: (2024)

RL4CO: an Extensive Reinforcement Learning for Combinatorial Optimization Benchmark
by: Berto, Federico, et al.
Published: (2023)