online optimization
A methodology for optimizing algorithms in a dynamic setting where data and conditions change over time. It allows models to adapt and learn incrementally rather than requiring retraining on static datasets.
- An Ellipsoid Algorithm for Online Convex Optimization
- Efficient and Near-Optimal Algorithm for Contextual Dueling Bandits with Offline Regression Oracles
- Hierarchical Optimization via LLM-Guided Objective Evolution for Mobility-on-Demand Systems
- Learning-Augmented Online Bipartite Fractional Matching
- Non-Clairvoyant Scheduling with Progress Bars
- Stochastic Regret Guarantees for Online Zeroth- and First-Order Bilevel Optimization
- Uniform Wrappers: Bridging Concave to Quadratizable Functions in Online Optimization