In this work we tackle the open problem of self-join size (SJS) estimation in a large-scale Distributed Data System, where tuples of a relation are distributed over data nodes whic...
With very noisy data, having plentiful samples eliminates overfitting in nonlinear regression, but not in nonlinear principal component analysis (NLPCA). To overcome this problem...
In many real-world scenarios, it is nearly impossible to collect explicit social network data. In such cases, whole networks must be inferred from underlying observations. Here, w...
Group communications (multicast) are foreseen to be one of the most critical yet challenging technologies to meet the exponentially growing demands for data distribution in a large...
It is of utmost importance for the network research community to have access to tools and testbeds to explore future directions for Internet traffic monitoring and engineering. Al...