Today's Internet is a massive, distributed network which continues to explode in size as e-
commerce and related activities grow. The heterogeneous and largely unregulated structure …

Delineating the tremendous growth in this area, the Handbook of Approximation Algorithms
and Metaheuristics covers fundamental, theoretical topics as well as advanced, practical …

The modeling and analysis of computer communications networks give rise to a variety of
interesting statistical problems. This chapter focuses on network tomography, a term used to …

Today's Internet is a massive, distributed network which continues to explode in size as e-
commerce and related activities grow. The heterogeneous and largely unregulated structure …

In network performance tomography, characteristics of the network interior, such as link loss
and packet latency, are inferred from correlated end-to-end measurements. Most work to …

Network tomography is a process for inferring" internal" link-level delay and loss
performance information based on end-to-end (edge) network measurements. These …

The statistical problem for network tomography is to infer the distribution of X, with mutually
independent components, from a measurement model Y= AX, where A is a given binary …

Inferring the routing topology and link performance from a node to a set of other nodes is an
important component in network monitoring and application design. In this paper, we …

Supervised learning is a classic data mining problem where one wishes to be be able to
predict an output value associated with a particular input vector. We present a new twist on …

This paper develops a new method for hierarchical clustering. Unlike other existing
clustering schemes, our method is based on a generative, tree-structured model that …