4 citations · 6 across the 3 of their papers we have counts for
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cs.LG2023★ 4 cited
Leveraging Factored Action Spaces for Efficient Offline Reinforcement Learning in Healthcare
Shengpu Tang, Maggie Makar, Michael W. Sjoding +2
Many reinforcement learning (RL) applications have combinatorial action spaces, where each action is a composition of sub-actions. A standard RL approach ignores this inherent fact…
cs.LG2022★ 2 cited
Disparate Censorship & Undertesting: A Source of Label Bias in Clinical Machine Learning
Trenton Chang, Michael W. Sjoding, Jenna Wiens
As machine learning (ML) models gain traction in clinical applications, understanding the impact of clinician and societal biases on ML models is increasingly important. While bias…