4 citations · 4 across the 4 of their papers we have counts for
4 papers
User Driven Model Adjustment via Boolean Rule Explanations
Elizabeth M. Daly, Massimiliano Mattetti, Öznur Alkan +1
AI solutions are heavily dependant on the quality and accuracy of the input training data, however the training data may not always fully reflect the most up-to-date policy landsca…
FROTE: Feedback Rule-Driven Oversampling for Editing Models
Öznur Alkan, Dennis Wei, Massimiliano Mattetti +3
Machine learning models may involve decision boundaries that change over time due to updates to rules and regulations, such as in loan approvals or claims management. However, in s…
Client Network: An Interactive Model for Predicting New Clients
Massimiliano Mattetti, Akihiro Kishimoto, Adi Botea +4
Understanding prospective clients becomes increasingly important as companies aim to enlarge their market bases. Traditional approaches typically treat each client in isolation, ei…
IRF: Interactive Recommendation through Dialogue
Oznur Alkan, Massimiliano Mattetti, Elizabeth M. Daly +2
Recent research focuses beyond recommendation accuracy, towards human factors that influence the acceptance of recommendations, such as user satisfaction, trust, transparency and s…