We explore algorithms to select actions in the causal bandit setting whe...
We propose functional causal Bayesian optimization (fCBO), a method for
...
We propose constrained causal Bayesian optimization (cCBO), an approach ...
We study the problem of globally optimizing the causal effect on a targe...
This paper studies the problem of performing a sequence of optimal
inter...
We study the problem of estimating potential revenue or demand at busine...
This paper studies the problem of learning the correlation structure of ...
This paper studies the problem of globally optimizing a variable of inte...
We propose a scalable framework for inference in an inhomogeneous Poisso...
We generalize the log Gaussian Cox process (LGCP) framework to model mul...