83 citations · 186 across the 17 of their papers we have counts for
3 papers · 1 filter
A general method for regularizing tensor decomposition methods via pseudo-data
Omer Gottesman, Weiwei Pan, Finale Doshi-Velez
Tensor decomposition methods allow us to learn the parameters of latent variable models through decomposition of low-order moments of data. A significant limitation of these algori…
Combining Parametric and Nonparametric Models for Off-Policy Evaluation
Omer Gottesman, Yao Liu, Scott Sussex +2
We consider a model-based approach to perform batch off-policy evaluation in reinforcement learning. Our method takes a mixture-of-experts approach to combine parametric and non-pa…
Improving Sepsis Treatment Strategies by Combining Deep and Kernel-Based Reinforcement Learning
Xuefeng Peng, Yi Ding, David Wihl +6
Sepsis is the leading cause of mortality in the ICU. It is challenging to manage because individual patients respond differently to treatment. Thus, tailoring treatment to the indi…