Multi-instance multi-label learning (MIML) is a framework for supervised classification where the objects to be classified are bags of instances associated with multiple labels....
We address the problem of weakly supervised semantic segmentation. The training images are labeled only by the classes they contain, not by their location in the image. On test im...
Alexander Vezhnevets, Vittorio Ferrari, Joachim M....
Multiple data sources containing different types of features may be available for a given task. For instance, users’ profiles can be used to build recommendation systems. In a...
—Ubiquitous smartphones are increasingly becoming the dominant platform for collaborative sensing. Smartphones, with their ever richer set of sensors, are being used to enable co...
Emmanouil Koukoumidis, Margaret Martonosi, Li-Shiu...
Consider a multithreaded parallel application running inside a multicore virtual machine context that is itself hosted on a multi-socket multicore physical machine. How should the...