Traditional feature selection methods assume that the data are independent and identically distributed (i.i.d.). In real world, tremendous amounts of data are distributed in a net...
This paper describes and evaluates privacy-friendly methods for extracting quasi-social networks from browser behavior on user-generated content sites, for the purpose of finding ...
Foster J. Provost, Brian Dalessandro, Rod Hook, Xi...
Social network systems, like last.fm, play a significant role in Web 2.0, containing large amounts of multimedia-enriched data that are enhanced both by explicit user-provided an...
Ioannis Konstas, Vassilios Stathopoulos, Joemon M....
We address the problem of classification in partially labeled networks (a.k.a. within-network classification) where observed class labels are sparse. Techniques for statistical re...
Brian Gallagher, Hanghang Tong, Tina Eliassi-Rad, ...
Max-margin Markov networks (M3 N) have shown great promise in structured prediction and relational learning. Due to the KKT conditions, the M3 N enjoys dual sparsity. However, the...