Kernel machines are a popular class of machine learning algorithms that achieve state of the art accuracies on many real-life classification problems. Kernel perceptrons are among...
Abstract— The goal of data center networking is to interconnect a large number of server machines with low equipment cost, high and balanced network capacity, and robustness to l...
Dan Li, Chuanxiong Guo, Haitao Wu, Kun Tan, Songwu...
Following recent work of Clarkson, we translate the coreset framework to the problems of finding the point closest to the origin inside a polytope, finding the shortest distance...
Abstract. ScaLAPACK is a library of high performance linear algebra routines for distributed memory MIMD computers. It is a continuation of the LAPACK project, which designed and p...
We develop new algorithms for learning monadic node selection queries in unranked trees from annotated examples, and apply them to visually interactive Web information extraction. ...