We consider the problem of numerical stability and model density growth when training a sparse linear model from massive data. We focus on scalable algorithms that optimize certain...
Abstract-- Identification of output error models from frequency domain data generally results in a non-convex optimization problem. A well-known method to approach the output error...
We provide a design of a control and management plane for data networks using the abstraction of 4D architecture, utilizing and extending 4D’s concept of a logically centralized...
—We present a framework to compute the visual hull of a polyhedral scene, in which the vertices of the polyhedra are given with some imprecision. Two kinds of visual event surfac...
—We consider a general wireless channel model for different types of code-division multiple access (CDMA) and space-division multiple-access (SDMA) systems with isometric random ...