This book provides a broad survey of models and efficient algorithms for Nonnegative Matrix
Factorization (NMF). This includes NMF's various extensions and modifications, especially …

Nonnegative matrix factorization (NMF) and its extensions such as Nonnegative Tensor
Factorization (NTF) have become prominent techniques for blind sources separation (BSS) …

In this paper, we extend and overview wide families of Alpha-, Beta-and Gamma-
divergences and discuss their fundamental properties. In literature usually only one single …

The rapidly increasing availability of electronic health records (EHRs) from multiple
heterogeneous sources has spearheaded the adoption of data-driven approaches for …

Roles represent node-level connectivity patterns such as star-center, star-edge nodes, near-
cliques or nodes that act as bridges to different regions of the graph. Intuitively, two nodes …

We propose a class of multiplicative algorithms for Nonnegative Matrix Factorization (NMF)
which are robust with respect to noise and outliers. To achieve this, we formulate a new …

The rapidly increasing availability of electronic health records (EHRs) from multiple
heterogeneous sources has spearheaded the adoption of data-driven approaches for …

Hyperspectral images contain mixed pixels due to low spatial resolution of hyperspectral
sensors. Spectral unmixing problem refers to decomposing mixed pixels into a set of …

Deep non-negative matrix factorization is committed to using multi-layer structure to extract
underlying parts-based representation. However, the basis images obtained by continuous …

In addition to hel** better understand how the human brain works, the brain-computer
interface neuroscience paradigm allows researchers to develop a new class of …