Joint and individual variation explained (JIVE) for integrated analysis of multiple data types

1 code implementation • 20 Feb 2011 • Eric F. Lock, Katherine A. Hoadley, J. S. Marron, Andrew B. Nobel

In this paper we introduce Joint and Individual Variation Explained (JIVE), a general decomposition of variation for the integrated analysis of such data sets.

A testing based extraction algorithm for identifying significant communities in networks

no code implementations • 3 Dec 2014 • James D. Wilson, Simi Wang, Peter J. Mucha, Shankar Bhamidi, Andrew B. Nobel

In addition, we carry out a simulation study to assess the effectiveness of ESSC in networks with various types of community structure, including networks with overlapping communities and those with background vertices.

Community Detection

Finding groups of cross-correlated features in bi-view data

1 code implementation • 10 Sep 2020 • Miheer Dewaskar, John Palowitch, Mark He, Michael I. Love, Andrew B. Nobel

A common problem in the exploratory analysis of such data is to identify groups of features of different data types that are strongly associated.

Alignment and Comparison of Directed Networks via Transition Couplings of Random Walks

2 code implementations • 13 Jun 2021 • Bongsoo Yi, Kevin O'Connor, Kevin McGoff, Andrew B. Nobel

Given two networks and a cost function relating their vertices, NetOTC finds a transition coupling of their associated random walks having minimum expected cost.