Research map / Learning theory and algorithms / Submodular and game algorithms
Non-Monotone DR-Submodular Function Maximization
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use Fast-DG with ε=0.5 instead of exact Double Greedy | DR-submodular revenue maximization · Adolescent health, Advogato, and Twitter lists | objective value | No clear effect |
| Use Fast-DG with ε=0.5 instead of Double Greedy | DR-submodular revenue maximization · Adolescent health, Advogato, and Twitter lists, large B | number of oracle calls: two or three orders of magnitude smaller | Helped |
| Use Lattice-DG instead of the DR-submodular methods | revenue maximization · Adolescent health, Advogato, and Twitter lists | objective value | Hurt |
Closest papers by meaning
- Online Non-Monotone DR-Submodular Maximization (AAAI 2021 · similarity 0.93)
- Optimal Algorithms for Continuous Non-monotone Submodular and DR-Submodular Maximization (NeurIPS 2018 · similarity 0.92)
- A Unified Approach for Maximizing Continuous DR-submodular Functions (NeurIPS 2023 · similarity 0.92)
- Greed is Still Good: Maximizing Monotone Submodular+Supermodular (BP) Functions (ICML 2018 · similarity 0.92)
- Online Two-Stage Submodular Maximization (NeurIPS 2025 · similarity 0.91)
- Consistent Submodular Maximization (ICML 2024 · similarity 0.90)
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