—The need to quickly and accurately classify Internet traffic for security and QoS control has been increasing significantly with the growing Internet traffic and applications ov...
Abstract. We address the problem of designing practical, energy-efficient protocols for data collection in wireless sensor networks using predictive modeling. Prior work has sugges...
We describe a part-based object-recognition framework, specialized to mining complex 3D objects from detailed 3D images. Objects are modeled as a collection of parts together with...
Abstract. Learning to act in an unknown partially observable domain is a difficult variant of the reinforcement learning paradigm. Research in the area has focused on model-free m...
Compressive sensing (CS) is an alternative to Shannon/Nyquist sampling for acquisition of sparse or compressible signals that can be well approximated by just K N elements from a...
Richard G. Baraniuk, Volkan Cevher, Marco F. Duart...