Kernel-based learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is perfor...
Gert R. G. Lanckriet, Nello Cristianini, Peter L. ...
The task of clustering is to identify classes of similar objects among a set of objects. The definition of similarity varies from one clustering model to another. However, in most ...
Abstract: Current peer-to-peer systems are network-agnostic, often generating large volumes of unnecessary inter-ISP traffic. Although recent work has shown the benefits of ISP-a...
—In this paper, we investigate the maximization of the coverage time for a clustered wireless sensor network (WSN) by optimal balancing of power consumption among cluster heads (...
Historically, compilers have operated by applying a fixed set of optimizations in a predetermined order. We call such an ordered list of optimizations a compilation sequence. This...
Keith D. Cooper, Devika Subramanian, Linda Torczon