This work proposes a novel approach for multiple time series forecasting. At first, multi-way
delay embedding transform (MDT) is employed to represent time series as low-rank block …

Malaria is a significant public health concern, with∼ 95% of cases occurring in Africa, but
accurate and timely diagnosis is problematic in remote and low-income areas. Here, we …

Tensor singular value decomposition (t-SVD) has recently become increasingly popular for
tensor recovery under partial and/or corrupted observations. However, the existing-SVD …

Night-time pedestrian retrieval is a cross-modality retrieval task of retrieving person images
between day-time visible images and night-time thermal images. It is a very challenging …

When solving dynamic multiobjective optimization problems, most evolutionary algorithms
attempt to predict the initial population in a new environment by mining the relationships …

Motivated by the fact that tensor robust principal component analysis (TRPCA) and its
variants do not utilize the actual rank value, which limits the recovery performance, and their …

Traditional approaches that represent observations in vector or matrix notation easily lead to
structure information losses and dependency destruction between elements. Tensors are …

Tensor factorization for recovering a tensor has been applied extensively in image
processing. The existing tensor factorization methods have shown effective performance …

Recently, predicting multivariate time-series (MTS) has attracted much attention to obtain
richer semantics with similar or better performances. In this paper, we propose a tri-partition …

Nonnegative Tucker Factorization (NTF) minimizes the euclidean distance or Kullback-
Leibler divergence between the original data and its low-rank approximation which often …