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...
Here we advocate an approach to learning hardware based on induction of finite state machines from temporal logic constraints. The method involves training on examples, constraint...
Marek A. Perkowski, Alan Mishchenko, Anatoli N. Ch...
Several algorithms have been proposed to learn to rank entities modeled as feature vectors, based on relevance feedback. However, these algorithms do not model network connections...
This paper presents a cooperative evolutionary approach for the problem of instance selection for instance based learning. The presented model takes advantage of one of the most r...
Within-network regression addresses the task of regression in partially labeled networked data where labels are sparse and continuous. Data for inference consist of entities associ...