3 papers
stat.AP2024
Bayesian Hierarchical Model for Synthesizing Registry and Survey Data on Female Breast Cancer Prevalence
Qiao Wang, Chester Lee Schmaltz, Jeannette Jackson-Thompson +4
In public health, it is critical for policymakers to assess the relationship between the disease prevalence and associated risk factors or clinical characteristics, facilitating ef…
stat.ML2020
Fully Bayesian Analysis of the Relevance Vector Machine Classification for Imbalanced Data
Wenyang Wang, Dongchu Sun, Zhuoqiong He
Relevance Vector Machine (RVM) is a supervised learning algorithm extended from Support Vector Machine (SVM) based on the Bayesian sparsity model. Compared with the regression prob…
cs.LG2020
Deep Neural Network in Cusp Catastrophe Model
Ranadeep Daw, Zhuoqiong He
Catastrophe theory was originally proposed to study dynamical systems that exhibit sudden shifts in behavior arising from small changes in input. These models can generate reasonab…