Research map / Bandits and online learning / Online convex optimization and games
Online Algorithms for Rent-Or-Buy with Expert Advice
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| use multiple experts (k up to 8) instead of one for consistent algorithm | consistent algorithm (Fig. 1) · ski rental simulations | competitive ratio | Helped |
| add robustness via minimum earliest buy time lambda*b (hybrid algorithm) | consistent algorithm · ski rental simulations, large prediction error | competitive ratio | Helped |
| add robustness via minimum earliest buy time lambda*b (hybrid algorithm) | consistent algorithm · ski rental simulations, small prediction error | competitive ratio | Hurt |
| randomized rather than deterministic algorithm for two experts | two-expert ski rental · zero prediction error | competitive ratio: 4/3 vs golden ratio 1.618 | Helped |
Closest papers by meaning
- Online Algorithms for Multi-shop Ski Rental with Machine Learned Advice (NeurIPS 2020 · similarity 0.92)
- Learning-Augmented Online Algorithm for Two-Level Ski-Rental Problem (AAAI 2024 · similarity 0.91)
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- Online Learning under Budget and ROI Constraints via Weak Adaptivity (ICML 2024 · similarity 0.85)
- Algorithms with Calibrated Machine Learning Predictions (ICML 2025 · similarity 0.84)
- Learning-Augmented Algorithms for the Bahncard Problem (NeurIPS 2024 · similarity 0.84)
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