Model-based decision support with uncertain human-centric data
Both human and algorithmic decision making can be complex. To truly intertwine the two, algorithms need to understand the human decision making process and humans need to have transparent understanding of algorithmic decision analytics. In this thesis, we leverage Bayesian Gaussian processes to be...
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Format: | Thesis |
Language: | English |
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2019
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