There is no doubt that big data are now rapidly expanding in all science and engineering
domains. While the potential of these massive data is undoubtedly significant, fully making …

The purpose of this research is to investigate the status and the evolution of the scientific
studies for the effect of social networks on big data and usage of big data for modeling the …

This article presents a powerful algorithmic framework for big data optimization, called the
block successive upper-bound minimization (BSUM). The BSUM includes as special cases …

Handbook of Robust Low-Rank and Sparse Matrix Decomposition: Applications in Image
and Video Processing shows you how robust subspace learning and tracking by …

The purpose of this research is to investigate the status and the evolution of the scientific
studies on the effect of social networks on e-commerce. The study seeks to address the …

A class of complex-valued adaptive filtering algorithms is proposed, with the aim to reduce
the cost of data processing in the complex domain. This is achieved by leveraging the …

This article investigates a distributed online learning problem with privacy preservation, in
which the learning nodes in a distributed network aims to minimize the sum of local loss …

A fundamental issue for statistical classification models in a streaming environment is that
the joint distribution between predictor and response variables changes over time (a …

On par with data-intensive applications, the sheer size of modern linear regression problems
creates an ever-growing demand for efficient solvers. Fortunately, a significant percentage of …

Almost every natural process is stochastic due to the basic consequences of nature's
existence and the dynamical behavior of each process that is not stationary but evolves with …