Research map / Learning theory and algorithms / Submodular and game algorithms
Streaming Non-Monotone Submodular Maximization: Personalized Video Summarization on the Fly
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use streaming SLS instead of the centralized exhaustive-search method | Video summarization with linear embeddings · YouTube | F-score: 57.8$\pm$0.5 -> 58.3$\pm$0.5 | No clear effect |
| Use streaming SLS instead of the centralized exhaustive-search method | Video summarization with linear embeddings · OVP | F-score: 75.5$\pm$0.4 -> 74.6$\pm$0.2 | Hurt |
| Use streaming SLS instead of AlgF | Video summarization with neural-network embeddings · YouTube | F-score: 60.3$\pm$0.5 -> 59.8$\pm$0.5 | No clear effect |
| Use streaming SLS instead of AlgF | Video summarization with neural-network embeddings · OVP | F-score: 78.0$\pm$0.5 -> 75.6$\pm$0.5 | Hurt |
| Use nonlinear rather than linear frame representations | Video summarization · YouTube | F-score: 57.8$\pm$0.5 -> 60.3$\pm$0.5 | Mixed |
| Use nonlinear rather than linear frame representations | Video summarization · OVP | F-score: 75.5$\pm$0.4 -> 77.7$\pm$0.4 | Mixed |
| Run SLS rather than the exhaustive-search method | Video summarization · YouTube and OVP | running time: 1700 times faster | Helped |
Closest papers by meaning
- Do Less, Get More: Streaming Submodular Maximization with Subsampling (NeurIPS 2018 · similarity 0.92)
- Streaming Submodular Maximization under a k-Set System Constraint (ICML 2020 · similarity 0.91)
- Streaming Robust Submodular Maximization: A Partitioned Thresholding Approach (NeurIPS 2017 · similarity 0.91)
- Online and Streaming Algorithms for Constrained k-Submodular Maximization (AAAI 2025 · similarity 0.89)
- Streaming Stochastic Submodular Maximization with On-Demand User Requests (NeurIPS 2025 · similarity 0.88)
- Deletion-Robust Submodular Maximization with Knapsack Constraints (AAAI 2024 · similarity 0.88)
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