IEEE

A Sparse Bayesian Learning-Based Approach With Indian Buffet Process Prior for Joint Wideband DOA and Frequency Band Estimation

Abstract: Sparse Bayesian learning (SBL)-based methods for wideband direction of arrival (DOA) estimation have shown impressive performance in terms of high resolution. It generally assumes that all ...
Scientific Research Publishing

Mai, T. T. (2024). A Sparse Pac-Bayesian Approach for High-Dimensional Quantile Prediction. Statistics and Computing, 35, Article No. 93.

ABSTRACT: Variable selection using penalized estimation methods in quantile regression models is an important step in screening for relevant covariates. In this paper, we present a one-step estimation ...
IEEE

Correlated Sparse Bayesian Learning for STAP: Algorithm and Dictionary

Abstract: Space-time adaptive processing (STAP) is a key technique for suppressing clutter. We develop a unified correlated sparse Bayesian learning (CSBL) framework to improve clutter suppression in ...
ascopubs.org

Bayesian Counterfactual Machine Learning Individualizes Radiation Modality Selection to Mitigate Immunosuppression

Tumor Site–Specific Radiation-Induced Lymphocyte Depletion Models After Fractionated Radiotherapy: Considerations of Model Structure From an Aggregate Data Meta-Analysis Lymphocytes play critical ...
GitHub

sparse-bayesian-learning

Add a description, image, and links to the sparse-bayesian-learning topic page so that developers can more easily learn about it.
GitHub

sparse-bayesian-learning

Contains a wide-ranging collection of compressed sensing and feature selection algorithms. Examples include matching pursuit algorithms, forward and backward stepwise regression, sparse Bayesian ...
Phys.org

Gaussian processes provide a new path toward quantum machine learning

Neural networks revolutionized machine learning for classical computers: self-driving cars, language translation and even artificial intelligence software were all made possible. It is no wonder, then ...