Research map / Learning theory and algorithms / Submodular and game algorithms
Streaming Robust Submodular Maximization: A Partitioned Thresholding Approach
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use STAR-T-Greedy on a robust summary after random removal of k summary elements | Dominating Set · ego-Twitter and Amazon product co-purchasing network | objective value | Helped |
| Use STAR-T-Greedy on a robust summary after greedy removal of 2k summary elements | Dominating Set · ego-Twitter and Amazon product co-purchasing network | objective value | Mixed |
| Use STAR-T-Greedy on the robust summary after restricting to drama movies | Personalized movie recommendation · MovieLens 1M, drama genre, user 445 | objective value | Hurt |
| Use STAR-T-Greedy on the robust summary after removing watched movies | Personalized movie recommendation · MovieLens 1M, 500 watched movies, user 445 | objective value | Hurt |
| Use STAR-T-Sieve instead of STAR-T-Greedy for the query-stage algorithm | STAR-T robust summary · Dominating Set | objective value | No clear effect |
| Choose the same number of items uniformly at random instead of using the robust summary | Dominating Set · ego-Twitter and Amazon product co-purchasing network | objective value | Hurt |
Closest papers by meaning
- Do Less, Get More: Streaming Submodular Maximization with Subsampling (NeurIPS 2018 · similarity 0.94)
- Streaming k-Submodular Maximization under Noise subject to Size Constraint (ICML 2020 · similarity 0.93)
- Robust Submodular Maximization: A Non-Uniform Partitioning Approach (ICML 2017 · similarity 0.92)
- Consistent Submodular Maximization (ICML 2024 · similarity 0.92)
- Deletion-Robust Submodular Maximization with Knapsack Constraints (AAAI 2024 · similarity 0.91)
- Online and Streaming Algorithms for Constrained k-Submodular Maximization (AAAI 2025 · similarity 0.89)
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