Daisee: Adaptive importance sampling by balancing exploration and exploitation

DOI10.1111/sjos.12637MaRDI QIDQ6049796

Unnamed Author, Yee Whye Teh, Tom Rainforth

Publication date: 11 October 2023

Published in: Scandinavian Journal of Statistics (Search for Journal in Brave)

zbMATH Keywords

banditimportance samplingadaptive Monte Carloexploration and exploitation

Mathematics Subject Classification ID

Statistics (62-XX)

Cites Work

• Families of alpha-, beta- and gamma-divergences: flexible and robust measures of similarities
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• Convergence rates for optimised adaptive importance samplers
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• Monte Carlo strategies in scientific computing.
• Weighted sums of certain dependent random variables
• Sequential Monte Carlo Methods in Practice
• Adaptive Multiple Importance Sampling
• Safe and Effective Importance Sampling
• Bandit Algorithms
• Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems
• Finite-time analysis of the multiarmed bandit problem
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