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05/12/2023
Nonparametric Bayesian inference for stochastic processes with piecewise constant priors
We present a survey of some of our recent results on Bayesian nonparamet...
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04/06/2023
Sharp Deviations Bounds for Dirichlet Weighted Sums with Application to analysis of Bayesian algorithms
In this work, we derive sharp non-asymptotic deviation bounds for weight...
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04/03/2023
Theoretical guarantees for neural control variates in MCMC
In this paper, we propose a variance reduction approach for Markov chain...
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03/14/2023
Fast Rates for Maximum Entropy Exploration
We consider the reinforcement learning (RL) setting, in which the agent ...
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11/03/2022
Statistical Inference for Scale Mixture Models via Mellin Transform Approach
This paper deals with statistical inference for the scale mixture models...
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10/01/2022
Primal-dual regression approach for Markov decision processes with general state and action space
We develop a regression based primal-dual martingale approach for solvin...
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09/28/2022
Optimistic Posterior Sampling for Reinforcement Learning with Few Samples and Tight Guarantees
We consider reinforcement learning in an environment modeled by an episo...
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06/20/2022
Simultaneous approximation of a smooth function and its derivatives by deep neural networks with piecewise-polynomial activations
This paper investigates the approximation properties of deep neural netw...
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06/14/2022
Variance Reduction for Policy-Gradient Methods via Empirical Variance Minimization
Policy-gradient methods in Reinforcement Learning(RL) are very universal...
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05/16/2022
From Dirichlet to Rubin: Optimistic Exploration in RL without Bonuses
We propose the Bayes-UCBVI algorithm for reinforcement learning in tabul...
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11/04/2021
Ex^2MCMC: Sampling through Exploration Exploitation
We develop an Explore-Exploit Markov chain Monte Carlo algorithm (Ex^2MC...
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07/01/2021
Semiparametric estimation of McKean-Vlasov SDEs
In this paper we study the problem of semiparametric estimation for a cl...
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01/30/2021
Rates of convergence for density estimation with GANs
We undertake a precise study of the non-asymptotic properties of vanilla...
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11/24/2020
Reinforced optimal control
Least squares Monte Carlo methods are a popular numerical approximation ...
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11/16/2020
Nonparametric Bayesian volatility estimation for gamma-driven stochastic differential equations
We study a nonparametric Bayesian approach to estimation of the volatili...
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08/03/2020
Estimating TVP-VAR models with time invariant long-run multipliers
The main goal of this paper is to develop a methodology for estimating t...
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02/03/2020
Randomized optimal stopping algorithms and their convergence analysis
In this paper we study randomized optimal stopping problems and consider...
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09/25/2019
Iterative Multilevel density estimation for McKean-Vlasov SDEs via projections
In this paper, we present a generic methodology for the efficient numeri...
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09/02/2019
Fourier transform MCMC, heavy tailed distributions and geometric ergodicity
Markov Chain Monte Carlo methods become increasingly popular in applied ...
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07/25/2019
Density deconvolution under general assumptions on the distribution of measurement errors
In this paper we study the problem of density deconvolution under genera...
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10/22/2018
Sparse constrained projection approximation subspace tracking
In this paper we revisit the well-known constrained projection approxima...
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08/07/2018
Optimal stopping via deeply boosted backward regression
In this note we propose a new approach towards solving numerically optim...
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04/30/2018
Nonparametric Bayesian inference for Lévy subordinators
Given discrete time observations over a growing time interval, we consid...
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10/30/2017