Many problems require repeated inference on probabilistic graphical models, with different values for evidence variables or other changes. Examples of such problems include utilit...
The study of complex networks led to the belief that the connectivity of network nodes generally follows a Power-law distribution. In this work, we show that modeling large-scale ...
Alessandra Sala, Haitao Zheng, Ben Y. Zhao, Sabrin...
Abstract--We present a novel and efficient algorithm, PATH COVERING, for solving the most reliable subgraph problem. A reliable subgraph gives a concise summary of the connectivity...
The paper develops a novel computational framework for predicting communication flow in social networks based on several contextual features. The problem is important because pred...
Munmun De Choudhury, Hari Sundaram, Ajita John, Do...
We study the flow control and routing decisions of self-interested users in a general congested network where a single profit-maximizing service provider sets prices for different ...