We propose a highly efficient framework for penalized likelihood kernel methods applied to multiclass models with a large, structured set of classes. As opposed to many previous a...
Linear support vector machines (SVM) are useful for classifying large-scale sparse data. Problems with sparse features are common in applications such as document classification a...
Service composition is emerging as an important paradigm for constructing distributed applications by combining and reusing independently developed component services. One key issu...
Given a set P of at most 2n − 4 prescribed edges (n ≥ 5) and vertices u and v whose mutual distance is odd, the n-dimensional hypercube Qn contains a hamiltonian path between ...
In cryptography, there has been tremendous success in building primitives out of homomorphic semantically-secure encryption schemes, using homomorphic properties in a blackbox way...