Early detection and diagnosis of the chiller sensor drift fault are crucial to maintain normal
operation for energy saving. Due to the complex physical structure and operation conditions …

Recently emerged technologies based on Deep Learning (DL) achieved outstanding results
on a variety of tasks in the field of Artificial Intelligence (AI). However, these encounter …

Clustering is a fundamental learning task with many applications in a wide range of fields.
Recently proposed techniques have shown that performing clustering in a discriminative …

Abstract Convolutional Kernel Networks (CKNs) are efficient multilayer kernel machines,
which are constructed by approximating a convolution kernel with a mapping based on …

The inability of new users to adapt quickly to the surface electromyography (sEMG) interface
has greatly hindered the development of sEMG in the field of rehabilitation. This is due …

Canonical Correlation Analysis (CCA) is widely used for multimodal data analysis and, more
recently, for discriminative tasks such as multi-view learning; however, it makes no use of …

This work proposes an interpretable multi-view deep neural network architecture, namely
optimal discriminant multi-view tensor convolutional network (ODMTCNet), by integrating …

Currently, deep neural networks (DNNs)-based models have drawn enormous attention and
have been utilized to different domains widely. However, due to the data-driven nature, the …

Pattern-set matching belongs to a class of problems where learning takes place through sets
rather than elements. Much used in computer vision, this approach has the advantage of …

In this paper, we present a distinct discriminant canonical correlation analysis network
(DDCCANet) based deep information quality representation with application to image …