research
∙
05/26/2023
On efficient covariate adjustment selection in causal effect estimation
In order to achieve unbiased and efficient estimators of causal effects ...
share
research
∙
05/26/2023
A novel framework extending cause-effect inference methods to multivariate causal discovery
We focus on the extension of bivariate causal learning methods into mult...
research
∙
12/07/2022
Bayesian multilevel multivariate logistic regression for superiority decision-making under observable treatment heterogeneity
In social, medical, and behavioral research we often encounter datasets ...
research
∙
09/08/2022
An Empirical Evaluation of Posterior Sampling for Constrained Reinforcement Learning
We study a posterior sampling approach to efficient exploration in const...
research
∙
06/08/2022
Bayesian multivariate logistic regression for superiority and inferiority decision-making under treatment heterogeneity
The effects of a treatment may differ between patients with different ch...
research
∙
02/14/2022
The Impact of Batch Learning in Stochastic Linear Bandits
We consider a special case of bandit problems, named batched bandits, in...
research
∙
11/03/2021
The Impact of Batch Learning in Stochastic Bandits
We consider a special case of bandit problems, namely batched bandits. M...
research
∙
08/21/2019
Exploring Offline Policy Evaluation for the Continuous-Armed Bandit Problem
The (contextual) multi-armed bandit problem (MAB) provides a formalizati...
research
∙
04/19/2019
Continuous-Time Birth-Death MCMC for Bayesian Regression Tree Models
Decision trees are flexible models that are well suited for many statist...
research
∙
11/06/2018
contextual: Evaluating Contextual Multi-Armed Bandit Problems in R
Over the past decade, contextual bandit algorithms have been gaining in ...
research
∙
02/28/2018
Maximum likelihood estimation of a finite mixture of logistic regression models in a continuous data stream
In marketing we are often confronted with a continuous stream of respons...
research
∙
10/15/2014