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 …

Big data is the concept of enormous amounts of data being generated daily in different fields
due to the increased use of technology and internet sources. Despite the various …

Recommendation and collaborative filtering systems are important in modern information
and e-commerce applications. As these systems are becoming increasingly popular in …

In the past decade, sparse and low-rank recovery has drawn much attention in many areas
such as signal/image processing, statistics, bioinformatics, and machine learning. To …

The heavy-tailed distributions of corrupted outliers and singular values of all channels in low-
level vision have proven effective priors for many applications such as background …

Nonnegative Matrix Factorization (NMF) has been one of the most widely used clustering
techniques for exploratory data analysis. However, since each data point enters the …

Multi-view spectral clustering has become appealing due to its good performance in
capturing the correlations among all views. However, on one hand, many existing methods …

Rapid advances in sensor, wireless communication, cloud computing and data science
have brought unprecedented amount of data to assist transportation engineers and …

Spectral clustering has attracted intensive attention in multimedia applications due to its
good performance on arbitrary shaped clusters and well-defined mathematical framework …

Low-rank modeling generally refers to a class of methods that solves problems by
representing variables of interest as low-rank matrices. It has achieved great success in …