Consistent High Dimensional Bayesian Variable

Consistent high-dimensional Bayesian variable selection via penalized credible regions

Speaker: Howard Bondell The Third Biannual Duke Workshop on Sensing and Analysis of

[AUTOML23] Computationally Efficient High-Dimensional Bayesian Optimization via Variable Selection

Authors: Yihang Shen, Carl Kingsford https://2023.automl.cc/program/accepted_papers/

Understanding High-Dimensional Bayesian Optimization

Title: Understanding

David Eriksson | "High-Dimensional Bayesian Optimization"

Abstract:

Raj Agrawal: "High-Dimensional Variable Selection & Nonlinear Interaction Discovery in Linear Time"

Title: "The SKIM-FA Kernel:

High dimensional gradient-augmented Bayesian optimization with adjoint solvers

We combine adjoint solvers with gradient-augmented

On the Consistency of Bayesian Variable Selection for High Dimensional Binary Regression and Classif

On the

Mean-field approximations for high-dimensional Bayesian Regression

Subhabrata Sen (Harvard University) https://simons.berkeley.edu/node/22591 Graph Limits, Nonparametric Models,...

Peng Chen - Projected Variational Methods for High-dimensional Bayesian Inference

It is a longstanding challenge to accurately and efficiently solve

Subhabrata Sen | Mean-field approximations for high-dimensional Bayesian regression

GRAMSIA 5/16/2023 Speaker: Subhabrata Sen (Harvard) Title: Mean-field approximations for

Lecture 15: Implementation of Bayesian Regression and Variable Selection

For access to lecture notes please visit: https://cics.nd.edu/education/current-courses/

Peng Chen: "Projected Stein variational methods for high-dimensional Bayesian inversion"

High Dimensional

The difficulty with real life Bayesian inference: high multidimensional integrals (and sums)

Since the