In this contribution, we explore the possibilities of learning in large-scale, multimodal processing systems operating under real-world conditions. Using an instance of a large-sca...
Due in part to the large volume of data available today, but more importantly to privacy concerns, data are often distributed across institutional, geographical and organizational...
When we talk about using neural networks for data mining we have in mind the original data mining scope and challenge. How did neural networks meet this challenge? Can we run neura...
In analyzing data from social and communication networks, we encounter the problem of classifying objects where there is an explicit link structure amongst the objects. We study t...
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, ...