learning-augmented algorithms
These algorithms integrate learning-based methods with traditional optimization techniques to enhance performance on complex problems. By using machine learning to inform algorithmic decisions, they aim to achieve better efficiency and results.
- A Learning-Augmented Approach to Online Allocation Problems
- Learning-Augmented Algorithms for $k$-median via Online Learning
- Learning-Augmented Online Bipartite Fractional Matching
- Learning-Augmented Streaming Algorithms for Correlation Clustering
- Non-Clairvoyant Scheduling with Progress Bars
- Robustifying Learning-Augmented Caching Efficiently without Compromising 1-Consistency