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, ...
Background: In vertebrates, a large part of gene transcriptional regulation is operated by cisregulatory modules. These modules are believed to be regulating much of the tissue-sp...
Hierarchical peer to peer networks with multiple directory services are an important architecture for large-scale file sharing due to their effectiveness and efficiency. Recent ...
We use unsupervised probabilistic machine learning ideas to try to explain the kinds of learning observed in real neurons, the goal being to connect abstract principles of self-or...
In typical classification tasks, we seek a function which assigns a label to a single object. Kernel-based approaches, such as support vector machines (SVMs), which maximize the ...