Bayesian Nonparametrics: An Alternative to Deep Learning

arXiv:2404.00085v1 Announce Type: new
Abstract: Bayesian nonparametric models offer a flexible and powerful framework for statistical model selection, enabling the adaptation of model complexity to the intricacies of diverse datasets. This survey intends to delve into the significance of Bayesian nonparametrics, particularly in addressing complex challenges across various domains such as statistics, computer science, and electrical engineering. By elucidating the basic properties and theoretical foundations of these nonparametric models, this survey aims to provide a comprehensive understanding of Bayesian nonparametrics …

abstract arxiv bayesian challenges complexity computer cs.lg datasets deep learning diverse domains enabling framework model selection significance statistical statistics stat.ml survey type