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12/01/2019
Interactive AI with a Theory of Mind
Understanding each other is the key to success in collaboration. For hum...
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11/01/2019
Probabilistic Formulation of the Take The Best Heuristic
The framework of cognitively bounded rationality treats problem solving ...
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10/21/2019
Making Bayesian Predictive Models Interpretable: A Decision Theoretic Approach
A salient approach to interpretable machine learning is to restrict mode...
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02/26/2019
Human-in-the-loop Active Covariance Learning for Improving Prediction in Small Data Sets
Learning predictive models from small high-dimensional data sets is a ke...
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10/05/2018
Local Interpretable Model-agnostic Explanations of Bayesian Predictive Models via Kullback-Leibler Projections
We introduce a method, KL-LIME, for explaining predictions of Bayesian p...
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09/08/2018
Modelling User's Theory of AI's Mind in Interactive Intelligent Systems
Many interactive intelligent systems, such as recommendation and informa...
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10/13/2017
User Modelling for Avoiding Overfitting in Interactive Knowledge Elicitation for Prediction
In human-in-the-loop machine learning, the user provides information bey...
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05/09/2017
Improving drug sensitivity predictions in precision medicine through active expert knowledge elicitation
Predicting the efficacy of a drug for a given individual, using high-dim...
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12/10/2016
Knowledge Elicitation via Sequential Probabilistic Inference for High-Dimensional Prediction
Prediction in a small-sized sample with a large number of covariates, th...
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12/07/2016