Although nonnegative matrix factorization (NMF) is widely used, some matrix factorization
methods result in misleading results and waste of computing resources due to lack of timely …

Aggregated network level modeling and control of traffic in urban networks have recently
gained a lot of interest due to unpredictability of travel behaviors and high complexity of …

Non-negative matrix factorization (NMF) has become a popular method for representing
meaningful data by extracting a non-negative basis feature from an observed non-negative …

As a novel paradigm for data mining and dimensionality reduction, Non-negative Matrix Tri-
Factorization (NMTF) has attracted much attention due to its notable performance and …

This article reports the study of algorithms for non-negative matrix factorization (NMF) in
various applications involving smoothly varying data such as time or temperature series …

To address the non-negativity dropout problem of quaternion models, a novel quasi non-
negative quaternion matrix factorization (QNQMF) model is presented for color image …

In this paper, based on the alternating nonnegative least squares framework, we present a
new efficient method for nonnegative matrix factorization that uses a quadratic regularization …

Abstract Non-negative Matrix Factorization (NMF) and its variants have been successfully
used for clustering text documents. However, NMF approaches like other models do not …

In this paper, we consider the graph regularization Q-weighted nonnegative matrix
factorization problem in multi-view clustering. Based on the Q-weighted norm property, this …

In this paper, we present an efficient method for nonnegative matrix factorization based on
the alternating nonnegative least squares framework. Our approach adopts a monotone …