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math.ST2026
Estimating conditional expectation
Hông Vân Lê
In this paper, we consider the problem of estimating conditional expectations as an ill-posed inverse problem. We propose a solution based on a generalization of Vapnik's theorem \…
math.ST2025
Batch learning equals online learning in Bayesian supervised learning
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In this paper we study Bayesian supervised learning models proposed by Lê in \cite{Le2025}. Using functoriality of probabilistic morphisms, we prove that sequential and batch Bayes…
math.ST2025
Probabilistic morphisms and Bayesian supervised learning
Hông Vân Lê
In this paper, we develop category theory of Markov kernels to study categorical aspects of Bayesian inversions. As a result, we present a unified model for Bayesian supervised lea…