Multi-label learning deals with data associated with multiple labels simultaneously. Previous work on multi-label learning assumes that for each instance, the "full" lab...
As computer architectures become increasingly complex, hand-tuning compiler heuristics becomes increasingly tedious and time consuming for compiler developers. This paper presents...
Matthew E. Taylor, Katherine E. Coons, Behnam Roba...
Modeling human behavior requires vast quantities of accurately labeled training data, but for ubiquitous people-aware applications such data is rarely attainable. Even researchers...
Daniel Peebles, Hong Lu, Nicholas D. Lane, Tanzeem...
Many problems in information extraction, text mining, natural language processing and other fields exhibit the same property: multiple prediction tasks are related in the sense th...
People tracking is a key technology for autonomous systems, intelligent cars and social robots operating in populated environments. What makes the task difficult is that the appea...
Luciano Spinello, Kai Oliver Arras, Rudolph Triebe...