The symmetric Nonnegative Matrix Factorization (NMF), a special but impo...
Tensor optimization is crucial to massive machine learning and signal
pr...
Systems of interacting agents can often be modeled as contextual games, ...
A growing trend in deep learning replaces fixed depth models by
approxim...
The (global) Lipschitz smoothness condition is crucial in establishing t...
Principal Component Analysis (PCA) is one of the most important methods ...
Symmetric nonnegative matrix factorization (NMF), a special but importan...
We study the convergence of a variant of distributed gradient descent (D...
This work investigates the geometry of a nonconvex reformulation of
mini...