Active and semi-supervised learning are important techniques when labeled data are scarce. Recently a method was suggested for combining active learning with a semi-supervised lea...
In this paper, we propose a multimodal Web image retrieval technique based on multi-graph enabled active learning. The main goal is to leverage the heterogeneous data on the Web t...
Device scaling trends dramatically increase the susceptibility of microprocessors to soft errors. Further, mounting demand for embedded microprocessors in a wide array of safety c...
Jason A. Blome, Shantanu Gupta, Shuguang Feng, Sco...
Code optimization and high level synthesis can be posed as constraint satisfaction and optimization problems, such as graph coloring used in register allocation. Graph coloring is...
Arathi Ramani, Fadi A. Aloul, Igor L. Markov, Kare...
Abstract. Multiple-instance learning (MIL) allows for training classifiers from ambiguously labeled data. In computer vision, this learning paradigm has been recently used in many ...