— This paper describes the winning entry to the IJCNN 2011 Social Network Challenge run by Kaggle.com. The goal of the contest was to promote research on realworld link predictio...
Arvind Narayanan, Elaine Shi, Benjamin I. P. Rubin...
An approach to semi-supervised learning is proposed that is based on a Gaussian random field model. Labeled and unlabeled data are represented as vertices in a weighted graph, wit...
: In dyadic prediction, the input consists of a pair of items (a dyad), and the goal is to predict the value of an observation related to the dyad. Special cases of dyadic predicti...
In this paper we address the problem of predicting when the available data is incomplete. We show that changing the generally accepted table-wise view of the sample items into a g...
Our dynamic graph-based relational mining approach has been developed to learn structural patterns in biological networks as they change over time. The analysis of dynamic network...