We address the problem of learning a kernel for a given supervised learning task. Our approach consists in searching within the convex hull of a prescribed set of basic kernels fo...
Andreas Argyriou, Raphael Hauser, Charles A. Micch...
In this work we consider the problem of monitoring information streams for anomalies in a scalable and efficient manner. We study the problem in the context of network streams wher...
We consider the dimensionality-reduction problem (finding a subspace approximation of observed data) for contaminated data in the high dimensional regime, where the number of obse...
An embedded, block-based, wavelet transform coding algorithm of low complexity is proposed. Three-Dimensional Set Partitioned Embedded bloCK(3D-SPECK) efficiently encodes hyperspe...
Datalink layer framing in wireless sensor networks usually faces a trade-off between large frame sizes for high channel bandwidth utilization and small frame sizes for effective e...
Raghu K. Ganti, Praveen Jayachandran, Haiyun Luo, ...