In this paper we describe the first stage of a new learning system for object detection and recognition. For our system we propose Boosting [5] as the underlying learning technique...
Andreas Opelt, Michael Fussenegger, Axel Pinz, Pet...
Abstract Current, data-driven applications have become more dynamic in nature, with the need to respond to events generated from distributed sources or to react to information extr...
A methodology for automatically identifying and clustering semantic features or topics in a heterogeneous text collection is presented. Textual data is encoded using a low rank no...
Farial Shahnaz, Michael W. Berry, V. Paul Pauca, R...
Recent work on anonymizing online social networks (OSNs) has looked at privacy preserving techniques for publishing a single instance of the network. However, OSNs evolve and a si...
Smriti Bhagat, Graham Cormode, Balachander Krishna...
Parallel dataflow programs generate enormous amounts of distributed data that are short-lived, yet are critical for completion of the job and for good run-time performance. We ca...
Steven Y. Ko, Imranul Hoque, Brian Cho, Indranil G...