A robust variant of binary search achieves regret O(C + log T) for dynamic pricing with known corruption C and O(C + log² T) when unknown.
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An algorithm for online resource allocation with budget and general constraints achieves O(sqrt(T)) regret in stochastic and alpha-regret in adversarial regimes with bounded constraint violations.
A new algorithm for online influence maximization under a total budget constraint using the independent cascade model and edge-level semi-bandit feedback, with improved regret bounds for both budgeted and cardinality settings.
citing papers explorer
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Toward Optimal Regret in Robust Pricing: Decoupling Corruption and Time
A robust variant of binary search achieves regret O(C + log T) for dynamic pricing with known corruption C and O(C + log² T) when unknown.
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Online Resource Allocation With General Constraints
An algorithm for online resource allocation with budget and general constraints achieves O(sqrt(T)) regret in stochastic and alpha-regret in adversarial regimes with bounded constraint violations.
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Budgeted Online Influence Maximization
A new algorithm for online influence maximization under a total budget constraint using the independent cascade model and edge-level semi-bandit feedback, with improved regret bounds for both budgeted and cardinality settings.