9 citations · 14 across the 4 of their papers we have counts for
4 papers
A Machine Learning Framework Towards Transparency in Experts' Decision Quality
Wanxue Dong, Maytal Saar-Tsechansky, Tomer Geva
Expert workers make non-trivial decisions with significant implications. Experts' decision accuracy is thus a fundamental aspect of their judgment quality, key to both management a…
Cost-Accuracy Aware Adaptive Labeling for Active Learning
Ruijiang Gao, Maytal Saar-tsechansky
Conventional active learning algorithms assume a single labeler that produces noiseless label at a given, fixed cost, and aim to achieve the best generalization performance for giv…
Modeling Longitudinal Dynamics of Comorbidities
Basil Maag, Stefan Feuerriegel, Mathias Kraus +2
In medicine, comorbidities refer to the presence of multiple, co-occurring diseases. Due to their co-occurring nature, the course of one comorbidity is often highly dependent on th…
Augmented Fairness: An Interpretable Model Augmenting Decision-Makers' Fairness
Tong Wang, Maytal Saar-Tsechansky
We propose a model-agnostic approach for mitigating the prediction bias of a black-box decision-maker, and in particular, a human decision-maker. Our method detects in the feature…