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Discovering User Types: Mapping User Traits by Task-Specific Behaviors in Reinforcement Learning
When assisting human users in reinforcement learning (RL), we can represent users as RL agents and study key parameters, called \emph{user traits}, to inform intervention design.
A Characterization of the Non-Uniqueness of Nonnegative Matrix Factorizations
Nonnegative matrix factorization (NMF) is a popular dimension reduction technique that produces interpretable decomposition of the data into parts.
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