Regularized least square regression with dependent samples

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Control functionals for Monte Carlo integration (2014, background): “roblems involving un-normalised densities ˇ, sampling is naturally facilitated by MCMC. Our theoretical analysis, which assumed IID samples, should be generalisable to this correlated sample setting (Sun and Wu, 2010). Moreover, state-of-the-art techniques for high-dimensional functional approximati”
A note on application of integral operator in learning theory (2009, methodology): “The resurgence of the kernel methods and the study of learning theory from an approximation point of view [5] have motivated a lot of research on this RKHS based regularization scheme [7,13,14,16,19].”
Regularization in reinforcement learning (2011, background): “For extensive surveys of this topic, refer to Szepesvári [2010]; Bertsekas [2010]; Buşoniu et al.”