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Online DR-Submodular Maximization: Minimizing Regret and Constraint Violation
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use OLFW with update rule (II) and concentration-based constraint margins | Online DR-submodular maximization with stochastic linear constraints · Online DR-submodular maximization with stochastic linear constraints (high probability) | (1-1/e)-regret: RT ≤ (LR²/2 + 2Rβ)√T | Helped |
| Use OLFW with update rule (II) and concentration-based constraint margins | Online DR-submodular maximization with stochastic linear constraints · Online DR-submodular maximization with stochastic linear constraints (high probability) | cumulative constraint violation: CT ≤ √(2G²T log(2T/ϵ)) + CRσ√(T log(2nT/ϵ)) + T/BT RβF√T + TRβ/BT (LR²/2 + 2Rβ) + Rβ | Helped |
| Use OLFW with update rule (I) | Online DR-submodular maximization with stochastic linear constraints · Online DR-submodular maximization with stochastic linear constraints (expectation) | (1-1/e)-regret: ˜O(T^(3/4)) | Helped |
| Use OLFW with update rule (I) | Online DR-submodular maximization with stochastic linear constraints · Online DR-submodular maximization with stochastic linear constraints (expectation) | cumulative constraint violation: E[CT ] ≤ T/BT RβF√T + R√Tr(Σ)√T + TRβ/BT (LR²/2 + 2Rβ) + Rβ | Helped |
Closest papers by meaning
- Gradient Methods for Online DR-Submodular Maximization with Stochastic Long-Term Constraints (NeurIPS 2024 · similarity 0.95)
- A Single Recipe for Online Submodular Maximization with Adversarial or Stochastic Constraints (NeurIPS 2020 · similarity 0.94)
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- From Linear to Linearizable Optimization: A Novel Framework with Applications to Stationary and Non-stationary DR-submodular Optimization (NeurIPS 2024 · similarity 0.89)
- Online and Streaming Algorithms for Constrained k-Submodular Maximization (AAAI 2025 · similarity 0.89)
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