The adaptive normal-hypergeometric-inverted-beta priors for sparse signals
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Statistical Computation and Simulation"
DOI: 10.1080/00949655.2020.1815199
Abstract: We investigate the estimation of high-dimensional normal mean under sparsity. Most shrinkage priors in the literature are based on certain assumptions of sparsity levels and signal sizes. Violation of these assumptions can lead to unsatisfactory… read more here.
Keywords: hypergeometric inverted; inverted beta; normal hypergeometric; adaptive normal ... See more keywords
Markov Chain Monte Carlo-Based Bayesian Inference for Learning Finite and Infinite Inverted Beta-Liouville Mixture Models
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DOI: 10.1109/access.2021.3078670
Abstract: Recently Inverted Beta-Liouville mixture models have emerged as an efficient paradigm for proportional positive vectors modeling and unsupervised learning. However, little attention has been devoted to investigate these generative models within discriminative classifiers. Our aim… read more here.
Keywords: liouville mixture; mixture models; inverted beta; beta liouville ... See more keywords
Bayesian Estimation of Inverted Beta Mixture Models With Extended Stochastic Variational Inference for Positive Vector Classification.
Sign Up to like & getrecommendations! Published in 2022 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2022.3213518
Abstract: The finite inverted beta mixture model (IBMM) has been proven to be efficient in modeling positive vectors. Under the traditional variational inference framework, the critical challenge in Bayesian estimation of the IBMM is that the… read more here.
Keywords: inverted beta; beta mixture; framework; bayesian estimation ... See more keywords