Research map / Bandits and online learning / Online convex optimization and games
Online Algorithms for Multi-shop Ski Rental with Machine Learned Advice
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use a trust parameter to trade reliance on prediction against worst-case protection | Deterministic and randomized MSSR algorithms with a single prediction · MSSR | competitive ratio | Mixed |
| Use customized randomized buying-time distributions incorporating shop prices | Randomized MSSR algorithm with a single prediction · Synthetic MSSR | competitive ratio | Helped |
| Set λ close to zero to trust predictions more | Single-prediction MSSR algorithms · Synthetic MSSR | competitive ratio | Mixed |
| Use multiple predictions and threshold their count | Deterministic MSSR algorithm with multiple predictions · Synthetic MSSR | competitive ratio | Mixed |
| Increase the number of predictions | Randomized MSSR algorithm with multiple predictions · Synthetic MSSR | competitive ratio | Mixed |
| Include the +1 term in the deterministic multiple-prediction break-even point (ablation) | Deterministic MSSR algorithm with multiple predictions · Synthetic MSSR | competitive ratio | Helped |
| Naively follow a single prediction without a robustness mechanism (ablation) | Simple learning-aided MSSR algorithm · MSSR | competitive ratio | Hurt |
| Use smaller λ, hence trust an erroneous prediction more | Single-prediction MSSR algorithm · Big Bang Theory season 12 viewer data | competitive ratio | Hurt |
| Use larger λ, hence trust predictions less | MSSR algorithms with multiple predictions · Synthetic MSSR | competitive ratio | Helped |
Closest papers by meaning
- Learning-Augmented Online Algorithm for Two-Level Ski-Rental Problem (AAAI 2024 · similarity 0.94)
- Improved Learning-Augmented Algorithms for the Multi-Option Ski Rental Problem via Best-Possible Competitive Analysis (ICML 2023 · similarity 0.93)
- Online Algorithms for Rent-Or-Buy with Expert Advice (ICML 2019 · similarity 0.92)
- Learning-Augmented Algorithms for the Bahncard Problem (NeurIPS 2024 · similarity 0.89)
- Algorithms with Calibrated Machine Learning Predictions (ICML 2025 · similarity 0.88)
- Online Algorithms with Uncertainty-Quantified Predictions (ICML 2024 · similarity 0.87)
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