4 papers
Decompounding Under General Mixing Distributions
Denis Belomestny, Ekaterina Morozova, Vladimir Panov
This study focuses on statistical inference for compound models of the form , where is a random variable denoting the count of summands, which are independe…
Model-free Posterior Sampling via Learning Rate Randomization
Daniil Tiapkin, Denis Belomestny, Daniele Calandriello +6
In this paper, we introduce Randomized Q-learning (RandQL), a novel randomized model-free algorithm for regret minimization in episodic Markov Decision Processes (MDPs). To the bes…
Forward Reverse Kernel Regression for the Schrödinger bridge problem
Denis Belomestny, John. Schoenmakers
In this paper, we study the Schrödinger Bridge Problem (SBP), which is central to entropic optimal transport. For general reference processes and begin--endpoint distributions, we…
Theoretical guarantees for neural control variates in MCMC
Denis Belomestny, Artur Goldman, Alexey Naumov +1
In this paper, we propose a variance reduction approach for Markov chains based on additive control variates and the minimization of an appropriate estimate for the asymptotic vari…