This article presents a form of bi-cross-validation (BCV) for choosing the rank in outer product models, especially the singular value decomposition (SVD) and the nonnegative matrix factorizationâ€¦ (More)

Network data often take the form of repeated interactions between senders and receivers tabulated over time. A primary question to ask of such data is which traits and behaviors are predictive ofâ€¦ (More)

The analysis of datasets taking the form of simple, undirected graphs continues to gain in importance across a variety of disciplines. Two choices of null model, the logistic-linear model and theâ€¦ (More)

Rank estimation is a classical model order selection problem that arises in a variety of important statistical signal and array processing systems, yet is addressed relatively infrequently in theâ€¦ (More)

This article presents a form of bi-cross-validation (BCV) for choosing the rank in outer product models, especially the singular value decomposition (SVD) and the non-negative matrix factorizationâ€¦ (More)

Recently, Mahoney and Orecchia demonstrated that popular diffusion-based procedures to compute a quick approximation to the first nontrivial eigenvector of a data graph Laplacian exactly solveâ€¦ (More)

In multivariate regression models we have the opportunity to look for hidden structure unrelated to the observed predictors. However, when one fits a model involving such latent variables it isâ€¦ (More)

A data set with n measurements on p variables can be represented by an n Ã— p data matrix X. In highdimensional settings where p is large, it is often desirable to work with a low-rank approximationâ€¦ (More)

Probabilistic methods for classifying text form a rich tradition in machine learning and natural language processing. For many important problems, however, class prediction is uninteresting becauseâ€¦ (More)