A key challenge in recommender system research is how to effectively profile new users, a problem generally known as cold-start recommendation. Recently the idea of progressivel...
We propose a general method to watermark and probabilistically identify the structured outputs of machine learning algorithms. Our method is robust to local editing operations and...
Ashish Venugopal, Jakob Uszkoreit, David Talbot, F...
Heterogeneous information networks that contain multiple types of objects and links are ubiquitous in the real world, such as bibliographic networks, cyber-physical networks, and ...
We propose a method for measuring the quality of a grouping result, based on the following observation: a better grouping result provides more information about the true, unknown g...
Erik A. Engbers, Michael Lindenbaum, Arnold W. M. ...
We study the problem of computing query results with confidence values in ULDBs: relational databases with uncertainty and lineage. ULDBs, which subsume probabilistic databases, o...