Advances in Loss-based, Penalized and Variational Bayesian Methods

Wed, Aug 6, 10:30 AM - 12:20 PM Room CC-103B Music City Center

Soham GhoshChair

Section on Bayesian Statistical Science

7 Presentations

A Bayesian decision-theoretic approach to sparse estimation

10:35 AM - 10:50 AM

Co-authors: Aihua Li, Surya Tokdar (Duke University), Aihua Li, Jason Xu (Duke University)

Decision theory Loss function Model selection Penalized least squares Sparse estimation Tuning parameter selection

A Class of Non-separable Penalty Functions for Bayesian Lasso-like Regression

10:50 AM - 11:05 AM

Co-authors: Christopher Hans (The Ohio State University), Christopher Hans (The Ohio State University)

Bayesian elastic net Bayesian lasso Penalized regression

Applying Multi-objective Bayesian optimization to Likelihood-Free inference

11:05 AM - 11:20 AM

Co-authors: Zichuan Chen (National University of Singapore), Zichuan Chen (National University of Singapore), Xinwei Li (National University of Singapore), Eui-jin Kim (Ajou University), Prateek Bansal (National University of Singapore), David Nott (National University of Singapore)

Likelihood-Free Inference Sequential Sampling Models Multi-objective Bayesian Optimization

Bayesian methods, meaningful parameters, and the importance of calibration

11:20 AM - 11:35 AM

Co-authors: Juhee Lee (UC Santa Cruz), Steven MacEachern (The Ohio State University), Hang Joon Kim (University of Cincinnati)

Bayes misspecified model sensitivity analysis generalized Bayes robust model

Sample continuation in bayesian hierarchical model via variational inference

11:35 AM - 11:50 AM

Co-authors: Yucong Liu (Georgia Institute of Technology), Zilai Si (Northwestern University), Yucong Liu (Georgia Institute of Technology), Alexander Strang (University of California, Berkeley)

Bayesian Hierarchical model Variational Inference Distribution Evolution

Loss-Based Bayesian Clustering for Big Data using Splinters

11:50 AM - 12:05 PM

Co-authors: David Dahl (Brigham Young University), David Dahl (Brigham Young University), Garritt Page (Brigham Young University), Fernando Quintana (Pontificia Universidad Catolica De Chile)

Bayesian clustering Decision theory Variation of information loss Binder loss Big data

Variational Bayes for Basis Selection in Functional Data Representation with Correlated Errors

12:05 PM - 12:20 PM

Co-authors: Ana Carolina da Cruz (University of Western Ontario), Camila De Souza (University of Western Ontario), Ana Carolina da Cruz (University of Western Ontario), Pedro Henrique Toledo de Oliveira Sousa (Federal University of Parana)

Bayesian inference Functional data Variational EM Basis function selection Correlated errors