Research map / Learning theory and algorithms / Submodular and game algorithms
The Power of Adaptivity for Stochastic Submodular Cover
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Allow more rounds of adaptivity | ParCA for stochastic set cover · Stochastic set cover, real-world datasets | expected cost | Helped |
| Use 6–7 rounds of adaptivity instead of full adaptivity | ParCA for stochastic set cover · Stochastic set cover, real-world datasets | expected cost | No clear effect |
| Allow more rounds of adaptivity | SParCA for optimal decision tree · Optimal decision tree, real-world and synthetic data | expected cost | Helped |
| Use about 6 rounds of adaptivity instead of full adaptivity | SParCA for optimal decision tree · Optimal decision tree, real-world and synthetic data | expected cost | No clear effect |
Closest papers by meaning
- Beyond Adaptive Submodularity: Approximation Guarantees of Greedy Policy with Adaptive Submodularity Ratio (ICML 2019 · similarity 0.90)
- Stochastic Submodular Maximization with Performance-Dependent Item Costs (AAAI 2019 · similarity 0.90)
- Online Two-Stage Submodular Maximization (NeurIPS 2025 · similarity 0.86)
- A Dynamic Algorithm for Weighted Submodular Cover Problem (ICML 2024 · similarity 0.85)
- Learning-Augmented Dynamic Submodular Maximization (NeurIPS 2024 · similarity 0.85)
- Consistent Submodular Maximization (ICML 2024 · similarity 0.85)
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