We consider the problem of metric learning for multi-view data and present a novel method for learning within-view as well as betweenview metrics in vector-valued kernel spaces, as a way to capture multi-modal structure of the data. We formulate two convex optimization problems to jointly learn the metric and the classifier or regressor in kernel feature spaces. An iterative three-step multi-vi...

We investigate reliable multi-path provisioning of traffic in high-capacity backbone mesh networks, e.g., nextgeneration SONET/SDH networks supporting virtual concatenation (VCAT). VCAT enables a connection to be inversely multiplexed on to multiple paths, a feature that may lead to significantly improved performance over conventional single-path provisioning. Other mesh networks such as those ...

Multi-constraint quality-of-service routing will become increasingly important as the Internet evolves to support real-time services. It is well known however, that optimum multi-constraint QoS routing is computationally complex, and for this reason various heuristics have been proposed for routing in practical situations. Among these methods, those that use a single mixed metric are the most p...

It is an outstanding problem to clarify how the RNA sequence is related to its structure and biological functions. We developed a simplified definition of a metric for tree representation of RNA secondary structures and analyzed the conformational energy landscapes of human spliceosomal snRNAs. We discuss the structural properties of the biological sequence by calculating the conformational ene...