In most natural and engineered systems, a set of entities interact with each other in
complicated patterns that can encompass multiple types of relationships, change in time and …

We provide the first information theoretical tight analysis for inference of latent community
structure given a sparse graph along with high dimensional node covariates, correlated with …

Statistical inference problems arising within signal processing, data mining, and machine
learning naturally give rise to hard combinatorial optimization problems. These problems …

The largest eigenvalue of a matrix is always larger or equal than its largest diagonal entry.
We show that for a class of random Laplacian matrices with independent off-diagonal …

We introduce a principled and theoretically sound spectral method for k-way clustering in
signed graphs, where the affinity measure between nodes takes either positive or negative …

The problem of synchronization over a group G aims to estimate a collection of group
elements G 1⁎,…, G n⁎∈ G based on noisy observations of a subset of all pairwise ratios of …

A central problem of random matrix theory is to understand the eigenvalues of spiked
random matrix models, in which a prominent eigenvector is planted into a random matrix …

Let G be a compact group and let fij∈ C (G). We define the non-unique games (NUG)
problem as finding g1,..., gn∈ G to minimize∑ ni, j= 1 fij (gig− 1 j). We introduce a convex …

Community detection in time series networks represents a timely and significant research
topic due to its applications in a broad range of scientific fields, including biology, social …

We propose a general framework for solving the group synchronization problem, where we
focus on the setting of adversarial or uniform corruption and sufficiently small noise …