Community detection is one of the popular research topics in the field of complex networks
analysis. It aims to identify communities, represented as cohesive subgroups or clusters …

Complementary to the fancy big data applications, networking for big data is an
indispensable supporting platform for these applications in practice. This emerging research …

X≈ WH, W∈ RM× R, H∈ RN× R,(1) to 'explain'the data matrix X, where W≥ 0, H≥ 0, and
R≤ min {M, N}. At first glance, NMF is nothing but an alternative factorization model to …

Imaging spectrometers measure electromagnetic energy scattered in their instantaneous
field view in hundreds or thousands of spectral channels with higher spectral resolution than …

Blind hyperspectral unmixing (HU), also known as unsupervised HU, is one of the most
prominent research topics in signal processing (SP) for hyperspectral remote sensing [1],[2] …

We consider the problem of finding a few representatives for a dataset, ie, a subset of data
points that efficiently describes the entire dataset. We assume that each data point can be …

The number of images associated with weakly supervised user-provided tags has increased
dramatically in recent years. User-provided tags are incomplete, subjective and noisy. In this …

In this paper, we study the nonnegative matrix factorization problem under the separability
assumption (that is, there exists a cone spanned by a small subset of the columns of the …

Identifying the underlying structure of a data set and extracting meaningful information is a
key problem in data analysis. Simple and powerful methods to achieve this goal are linear …

Finding an informative subset of a large collection of data points or models is at the center of
many problems in computer vision, recommender systems, bio/health informatics as well as …