Abstract: We study sample average approximations under adaptive importance sampling in which the sample densities may depend on previous random samples. Based on a generic uniform law of large numbers ...
This repository contains the research paper and code related to Uniform Convergence of Lipschitz Functions with Dependent Gaussian Samples. The work provides theoretical bounds for learning Lipschitz ...
We analyse the performance of a recursive Monte Carlo method for the Bayesian estimation of the static parameters of a discrete-time state-space Markov model. The algorithm employs two layers of ...
Abstract: We consider deep neural networks (DNNs) with a Lipschitz continuous activation function and with weight matrices of variable widths. We establish a uniform convergence analysis framework in ...
Abstract. In this work, we discuss various kinds of ℐ₂-uniform convergence for double sequences of functions and introduce the concepts of ℐ₂ and ℐ 2 ∗ -uniform convergence, ℐ₂-uniformly Cauchy ...
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