Multiple Instance Learning (MIL) provides a framework for training a discriminative classifier from data with ambiguous labels. This framework is well suited for the task of learni...
Carolina Galleguillos, Boris Babenko, Andrew Rabin...
The increased use of context for high level reasoning has been popular in recent works to increase recognition accuracy. In this paper, we consider an orthogonal application of con...
We consider trails to be a document type of growing importance, authored in abundance as locative technologies become embedded in mobile devices carried by billions of humans. As ...
The capability of performing architectural exploration has become essential for embedded microprocessor design in System-On-Chip. While many retargetable instruction set (ISA) sim...
RELIEF is considered one of the most successful algorithms for assessing the quality of features. In this paper, we propose a set of new feature weighting algorithms that perform s...