Research map / Learning theory and algorithms / Submodular and game algorithms
The Power of Optimization from Samples
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| estimate marginal contributions from samples and return best of top-k set and random set (Algorithm 1) versus random set baseline | monotone submodular functions with curvature c under cardinality constraint · synthetic hard instances | objective value | Helped |
| curvature increase (c from 0 toward 1) | Algorithm 1 solution quality · synthetic hard instances | objective value | Hurt |
Closest papers by meaning
- Approximation Guarantees for Adaptive Sampling (ICML 2018 · similarity 0.92)
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- Optimization for Approximate Submodularity (NeurIPS 2018 · similarity 0.91)
- Consistent Submodular Maximization (ICML 2024 · similarity 0.89)
- An Asymptotically Optimal Approximation Algorithm for Multiobjective Submodular Maximization at Scale (ICML 2025 · similarity 0.88)
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