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SCAFFLSA: Quantifying and Eliminating Heterogeneity Bias in Federated Linear Stochastic Approximation and Temporal Difference Learning., , , , , , and . CoRR, (2024)Demonstration-Regularized RL., , , , , , , and . CoRR, (2023)Finite Time Analysis of Linear Two-timescale Stochastic Approximation with Markovian Noise., , , , and . COLT, volume 125 of Proceedings of Machine Learning Research, page 2144-2203. PMLR, (2020)Variance reduction for Markov chains with application to MCMC., , , , and . Stat. Comput., 30 (4): 973-997 (2020)Theoretical guarantees for neural control variates in MCMC., , , and . CoRR, (2023)Model-free Posterior Sampling via Learning Rate Randomization., , , , , , , , and . CoRR, (2023)Tight High Probability Bounds for Linear Stochastic Approximation with Fixed Stepsize., , , , , and . NeurIPS, page 30063-30074. (2021)Improving the discoverability, accessibility, and citability of omics datasets: a case report., , , , , and . JAMIA, 24 (2): 388-393 (2017)First Order Methods with Markovian Noise: from Acceleration to Variational Inequalities., , , , , and . CoRR, (2023)Simultaneous approximation of a smooth function and its derivatives by deep neural networks with piecewise-polynomial activations., , , and . CoRR, (2022)