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math.ST2018
Rademacher complexity for Markov chains : Applications to kernel smoothing and Metropolis-Hasting
Patrice Bertail, François Portier
Following the seminal approach by Talagrand, the concept of Rademacher complexity for independent sequences of random variables is extended to Markov chains. The proposed notion of…
math.ST2016★ 3 cited
Practical targeted learning from large data sets by survey sampling
Patrice Bertail, Antoine Chambaz, Emilien Joly
We address the practical construction of asymptotic confidence intervals for smooth (i.e., path-wise differentiable), real-valued statistical parameters by targeted learning from i…