69 citations · 93 across the 11 of their papers we have counts for
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cs.HC2023
Co-creating a globally interpretable model with human input
Rahul Nair
We consider an aggregated human-AI collaboration aimed at generating a joint interpretable model. The model takes the form of Boolean decision rules, where human input is provided…
cs.HC2023★ 10 cited
AutoDOViz: Human-Centered Automation for Decision Optimization
Daniel Karl I. Weidele, Shazia Afzal, Abel N. Valente +12
We present AutoDOViz, an interactive user interface for automated decision optimization (AutoDO) using reinforcement learning (RL). Decision optimization (DO) has classically being…
cs.HC2021★ 69 cited
Neo: Generalizing Confusion Matrix Visualization to Hierarchical and Multi-Output Labels
Jochen Görtler, Fred Hohman, Dominik Moritz +5
The confusion matrix, a ubiquitous visualization for helping people evaluate machine learning models, is a tabular layout that compares predicted class labels against actual class…