Large amounts of multidimensional data represented by multiway arrays or tensors are
prevalent in modern applications across various fields such as chemometrics, genomics …

High-order clustering aims to identify heterogeneous substructures in multiway datasets that
arise commonly in neuroimaging, genomics, social network studies, etc. The non-convex …

In this paper, we consider the singular values and singular vectors of low rank perturbations
of large rectangular random matrices, in the regime the matrix is “long”: we allow the number …

In this paper, we study the power iteration algorithm for the asymmetric spiked tensor model,
as introduced in Richard and Montanari (2014). We give necessary and sufficient conditions …

This paper studies a general framework for high-order tensor SVD. We propose a new
computationally efficient algorithm, tensor-train orthogonal iteration (TTOI), that aims to …

The paper introduces the DIverse MultiPLEx Generalized Random Dot Product Graph
(DIMPLE-GRDPG) network model where all layers of the network have the same collection …

The paper introduces a Signed Generalized Random Dot Product Graph (SGRDPG) model,
which is a variant of the Generalized Random Dot Product Graph (GRDPG), where, in …

Higher-order multiway data is ubiquitous in machine learning and statistics and often
exhibits community-like structures, where each component (node) along each different …

The quantum approximate optimization algorithm (QAOA) is a general-purpose algorithm for
combinatorial optimization. In this paper, we analyze the performance of the QAOA on a …

Higher-order multiway data is ubiquitous in machine learning and statistics and often
exhibits community-like structures, where each component (node) along each different …