Within-network regression addresses the task of regression in partially labeled networked data where labels are sparse and continuous. Data for inference consist of entities associ...
Visualizing network data, from tree structures to arbitrarily connected graphs, is a difficult problem in information visualization. A large part of the problem is that in network...
Galileo Namata, Brian Staats, Lise Getoor, Ben Shn...
Following the exponential growth of social media, there now exist huge repositories of videos online. Among the huge volumes of videos, there exist large numbers of near-duplicate...
Abstract: Structure learning of dynamic Bayesian networks provide a principled mechanism for identifying conditional dependencies in time-series data. This learning procedure assum...
This paper describes the results of a 500 million packet trace of a popular on-line, multi-player, game server. The results show that the traffic behavior of this heavily loaded ga...
Francis Chang, Wu-chang Feng, Wu-chi Feng, Jonatha...