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Refined Thompson Learning for Adaptive Bandits: Power-Efficient Flexibility Scheduling Across Data Centers
Arxiv
0+阅读 · 8月29日
The Optimizer Is the Agent: Reasoning-Driven Search across Prompts, Programs, and ML Workflows
Arxiv
0+阅读 · 8月31日
Mixture-Greedy for Online Generative Model Selection: Is UCB Necessary in Diversity-Aware Multi-Armed Bandits?
Arxiv
0+阅读 · 8月30日
Budget-Constrained Causal Bandits: Bridging Uplift Modeling and Sequential Decision-Making
Arxiv
0+阅读 · 8月28日
Information Routing across Batch Boundaries: Memory--Batch Tradeoffs in Lipschitz Bandits
Arxiv
0+阅读 · 8月8日
Refined Thompson Learning for Adaptive Bandits: Sustainable Power-Efficient Flexibility Scheduling Across Data Centers
Arxiv
0+阅读 · 8月2日
Does 1/2-Tsallis-INF Also Work Well for Best-Arm Identification?
Arxiv
0+阅读 · 8月15日
Practical and Optimal Algorithm for Linear Contextual Bandits with Rare Parameter Updates
Arxiv
0+阅读 · 8月15日
Practical and Optimal Algorithm for Linear Contextual Bandits with Rare Parameter Updates
Arxiv
0+阅读 · 8月22日
The Price of Decentralization in Top-$K$ Arm Identification
Arxiv
0+阅读 · 8月22日
Impatient Bandits: Optimizing for the Long-Term Without Delay
Arxiv
0+阅读 · 6月22日
Minimax Quantile Lower Bounds for Interactive Statistical Decision Making with Privacy
Arxiv
0+阅读 · 6月22日
Improved Algorithms for Nash Welfare in Linear Bandits
Arxiv
0+阅读 · 6月21日
A Jointly Efficient and Optimal Algorithm for Heteroskedastic Generalized Linear Bandits with Adversarial Corruptions
Arxiv
0+阅读 · 6月22日
Adaptive Prior Selection in Gaussian Process Bandits with Thompson Sampling
Arxiv
0+阅读 · 6月8日
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