Urban big data fusion creates huge values for urban computing in solving urban problems.
In recent years, various models and algorithms based on deep learning have been …

Visual Sentiment Analysis aims to understand how images affect people, in terms of evoked
emotions. Although this field is rather new, a broad range of techniques have been …

A panoply of multi-view clustering algorithms has been developed to deal with prevalent
multi-view data. Among them, spectral clustering-based methods have drawn much attention …

In this work, we investigate the problem of learning knowledge from the massive community-
contributed images with rich weakly-supervised context information, which can benefit …

Anomaly detection of hyperspectral data has been gaining particular attention for its ability in
detecting targets in an unsupervised manner. Autoencoder (AE), together with its variants …

Multiview clustering has gained increasing attention recently due to its ability to deal with
multiple sources (views) data and explore complementary information between different …

Linear discriminant analysis (LDA) is a very popular supervised feature extraction method
and has been extended to different variants. However, classical LDA has the following …

Graphs have become increasingly popular in modeling structures and interactions in a wide
variety of problems during the last decade. Graph-based clustering and semi-supervised …

Intelligent data-driven fault diagnosis methods for rolling element bearings have been
widely developed in the recent years. In real industries, the collected machinery signals are …

Machine learning methods have achieved good performance and been widely applied in
various real-world applications. They can learn the model adaptively and be better fit for …