solution quality
Solution quality refers to the effectiveness and optimality of a generated output by an AI model when applied to a problem. High solution quality is desired for tasks ranging from scheduling to resource allocation.
- Hybrid-Balance GFlowNet for Solving Vehicle Routing Problems
- Improved Algorithms for Overlapping and Robust Clustering of Edge-Colored Hypergraphs: An LP-Based Combinatorial Approach
- Individually Fair Diversity Maximization
- Inexact Column Generation for Bayesian Network Structure Learning via Difference-of-Submodular Optimization
- Learning to Condition: A Neural Heuristic for Scalable MPE Inference
- Learning to Insert for Constructive Neural Vehicle Routing Solver
- MLZero: A Multi-Agent System for End-to-end Machine Learning Automation
- Solver-Free Decision-Focused Learning for Linear Optimization Problems
- Solver-Informed RL: Grounding Large Language Models for Authentic Optimization Modeling
- Towards Unsupervised Training of Matching-based Graph Edit Distance Solver via Preference-aware GAN