Recommendation strategies are typically evaluated by using previously lo...
Captions are crucial for understanding scientific visualizations and
doc...
Recommender systems aim to answer the following question: given the item...
We study the problem of off-policy evaluation from batched contextual ba...
We consider adaptive designs for a trial involving N individuals that we...
We study the problem of off-policy evaluation for slate bandits, for the...
We generalize the proximal g-formula of Miao, Geng, and Tchetgen Tchetge...
We study the problem of off-policy evaluation (OPE) in Reinforcement Lea...
We address the problem of finding an optimal policy in a Markov decision...
Posterior sampling for reinforcement learning (PSRL) is a popular algori...
We describe a new method called t-ETE for finding a low-dimensional embe...
We consider the problem of approximate joint triangularization of a set ...
Decision-theoretic planning is a popular approach to sequential decision...