Online Matrix Factorization (OMF) is a fundamental tool for dictionary learning problems,
giving an approximate representation of complex data sets in terms of a reduced number of …

Researchers in many fields use networks to represent interactions between entities in
complex systems. To study the large-scale behavior of complex systems, it is useful to …

Online Tensor Factorization (OTF) is a fundamental tool in learning low-dimensional
interpretable features from streaming multi-modal data. While various algorithmic and …

Dictionary learning (DL), implemented via matrix factorization (MF), is commonly used in
computational biology to tackle ubiquitous clustering problems. The method is favored due …

We focus on analyzing the classical stochastic projected gradient methods under a general
dependent data sampling scheme for constrained smooth nonconvex optimization. We show …

A system of coupled oscillators on an arbitrary graph is locally driven by the tendency to
mutual synchronization between nearby oscillators, but can and often exhibit nonlinear …

Exchangeable random graphs, which include some of the most widely studied network
models, have emerged as the mainstay of statistical network analysis in recent years …

Stochastic majorization-minimization (SMM) is a class of stochastic optimization algorithms
that proceed by sampling new data points and minimizing a recursive average of surrogate …

arXiv:2001.00278v2 [cs.LG] 6 Jan 2020 Page 1 arXiv:2001.00278v2 [cs.LG] 6 Jan 2020 MOTIVIC
CLUSTERING SCHEMES FOR DIRECTED GRAPHS FACUNDO MÉMOLI AND GUILHERME …

Motivation Genomes of multicellular systems are compartmentalized and dynamically folded
within the three-dimensional (3D) confines of the nucleus in order to facilitate gene …