Most frameworks for utility elicitation assume a predefined set of features over which user preferences are expressed. We consider utility elicitation in the presence of subjecti...
Utility or preference elicitation is a critical component in many recommender and decision support systems. However, most frameworks for elicitation assume a predefined set of fe...
Most models of utility elicitation in decision support and interactive optimization assume a predefined set of "catalog" features over which user preferences are express...
Recent algorithms provide powerful solutions to the problem of determining cost-minimizing (or revenue-maximizing) allocations of items in combinatorial auctions. However, in many...
Active learning (AL) is an increasingly popular strategy for mitigating the amount of labeled data required to train classifiers, thereby reducing annotator effort. We describe ...
Byron C. Wallace, Kevin Small, Carla E. Brodley, T...