In this paper, we introduce a generic framework for semi-supervised kernel learning. Given pairwise (dis-)similarity constraints, we learn a kernel matrix over the data that respe...
The need for flexible forms of serialisation arises under many circumstances, e.g. for doing high-level inter-process communication or to achieve persistence. Many languages, inc...
Graph-theoretic abstractions are extensively used to analyze massive data sets. Temporal data streams from socioeconomic interactions, social networking web sites, communication t...
— For a wide variety of sensor network environments, location information is unavailable or expensive to obtain. We propose a location-free, lightweight, distributed, and data-ce...
Large-scale multimedia semantic concept detection requires realtime identification of a set of concepts in streaming video or large image datasets. The potentially high data volum...
Deepak S. Turaga, Rong Yan, Olivier Verscheure, Br...