The random dot product graph (RDPG) is an independent-edge random graph that is
analytically tractable and, simultaneously, either encompasses or can successfully …

Spectral methods have emerged as a simple yet surprisingly effective approach for
extracting information from massive, noisy and incomplete data. In a nutshell, spectral …

While many statistical models and methods are now available for network analysis,
resampling of network data remains a challenging problem. Cross-validation is a useful …

Identifying and tracking community structures in complex networks are one of the
cornerstones of network studies, spanning multiple disciplines, from statistics to machine …

The development of models and methodology for the analysis of data from multiple
heterogeneous networks is of importance both in statistical network theory and across a …

Inference problems with conjectured statistical-computational gaps are ubiquitous
throughout modern statistics, computer science, statistical physics and discrete probability …

We present a simple and flexible method to prove consistency of semidefinite optimization
problems on random graphs. The method is based on Grothendieck's inequality. Unlike the …

Impact of regularization on spectral clustering Page 1 The Annals of Statistics 2016, Vol. 44, No.
4, 1765–1791 DOI: 10.1214/16-AOS1447 © Institute of Mathematical Statistics, 2016 IMPACT …

We consider multi-layer network data where the relationships between pairs of elements are
reflected in multiple modalities, and may be described by multivariate or even high …

Denote by A the adjacency matrix of an Erdos-Renyi graph with bounded average degree.
We consider the problem of maximizing< A-EA, X> over the set of positive semidefinite …