We consider the problem of causal effect estimation with an unobserved
c...
We consider the estimation of average and counterfactual treatment effec...
We study a nonparametric approach to Bayesian computation via feature me...
We propose kernel ridge regression estimators for mediation analysis and...
Proxy causal learning (PCL) is a method for estimating the causal effect...
We show that the popular reinforcement learning (RL) strategy of estimat...
Instrumental variable (IV) regression is a standard strategy for learnin...
We propose a novel framework for non-parametric policy evaluation in sta...
In real-world classification problems, pairwise supervision (i.e., a pai...
Uncoupled regression is the problem to learn a model from unlabeled data...
We study the problem of stochastic combinatorial pure exploration (CPE),...
We consider a problem of learning a binary classifier only from positive...
We formulate and study a novel multi-armed bandit problem called the
qua...
We propose the first fully-adaptive algorithm for pure exploration in li...