23 citations · 64 across the 6 of their papers we have counts for
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cs.HC2017★ 9 cited
User Modelling for Avoiding Overfitting in Interactive Knowledge Elicitation for Prediction
Pedram Daee, Tomi Peltola, Aki Vehtari +1
In human-in-the-loop machine learning, the user provides information beyond that in the training data. Many algorithms and user interfaces have been designed to optimize and facili…
cs.AI2017★ 17 cited
Improving drug sensitivity predictions in precision medicine through active expert knowledge elicitation
Iiris Sundin, Tomi Peltola, Muntasir Mamun Majumder +6
Predicting the efficacy of a drug for a given individual, using high-dimensional genomic measurements, is at the core of precision medicine. However, identifying features on which…