mlsanityData to 13 Oct 2026

Unbiased Multilevel Monte Carlo: Stochastic Optimization, Steady-state Simulation, Quantiles, and Other Applications

arXiv 1904.09929 ↗First posted 22 Apr 2019math.ST math.OC stat.COcited by 17

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Abstract (arXiv)

We present general principles for the design and analysis of unbiased Monte Carlo estimators in a wide range of settings. Our estimators posses finite work-normalized variance under mild regularity conditions. We apply our estimators to various settings of interest, including unbiased optimization in Sample Average Approximations, unbiased steady-state simulation of regenerative processes, quantile estimation and nested simulation problems.

Key facts. Cited by 17 papers in the map (data through 13 Oct 2026). First posted on arXiv 22 Apr 2019.

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Citing papers per year: 2021: 1; 2022: 2; 2023: 3; 2024: 4; 2025: 6; 2026: 1.

17 papers.

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  1. 2023A Finite Sample Complexity Bound for Distributionally Robust Q-learningcited by 35
  2. 2021Stochastic Bias-Reduced Gradient Methodscited by 25
  3. 2023Model-Free Robust Average-Reward Reinforcement Learningcited by 20
  4. 2022Distributionally Robust Optimization via Ball Oracle Accelerationcited by 14
  5. 2024Model-Free Robust Reinforcement Learning with Sample Complexity Analysiscited by 9
  6. 2022Constructing unbiased gradient estimators with finite variance for conditional stochastic optimizationcited by 6
  7. 2025Finite-Sample Analysis of Policy Evaluation for Robust Average Reward Reinforcement Learningcited by 6
  8. 2023Bayesian Risk-Averse Q-Learning with Streaming Observationscited by 4
  9. 2024Multi-level Monte-Carlo Gradient Methods for Stochastic Optimization with Biased Oraclescited by 4
  10. 2024Prediction-Enhanced Monte Carlo: A Machine Learning View on Control Variatecited by 2
  11. 2025Planning and Learning in Average Risk-aware MDPscited by 2
  12. 2025Pessimism Principle Can Be Effective: Towards a Framework for Zero-Shot Transfer Reinforcement Learningcited by 2
5 more
  1. 2024Unbiased least squares regression via averaged stochastic gradient descentcited by 1
  2. 2026Multilevel and Sequential Monte Carlo for Training-Free Diffusion Guidancecited by 1
  3. 2025Quantum speedup of non-linear Monte Carlo problemscited by 0
  4. 2025Duality and Policy Evaluation in Distributionally Robust Bayesian Diffusion Controlcited by 0
  5. 2025Benchmarking Stochastic Approximation Algorithms for Fairness-Constrained Training of Deep Neural Networkscited by 0