During the last decades, smart tactile sensing systems based on different sensing
techniques have been developed due to their high potential in industry and biomedical …

The Internet of Things (IoT) is enabled by the latest developments in smart sensors,
communication technologies, and Internet protocols with broad applications. Collecting data …

Conventional multiview clustering seeks to partition data into respective groups based on
the assumption that all views are fully observed. However, in practical applications, such as …

Incomplete multi-view clustering aims to exploit the information of multiple incomplete views
to partition data into their clusters. Existing methods only utilize the pair-wise sample …

An important underlying assumption that guides the success of the existing multiview
learning algorithms is the full observation of the multiview data. However, such rigorous …

In this paper, a new deep incomplete multi-view clustering network, called DIMC-net, is
proposed to address the challenge of multi-view clustering on missing views. In particular …

In this paper, we propose a general framework for incomplete multiview clustering. The
proposed method is the first work that exploits the graph learning and spectral clustering …

Due to the rapid development of multimedia technology and sensor technology, multi-view
clustering (MVC) has become a research hotspot in machine learning, data mining, and …

We propose a mechanism to use data with missing values for designing classifiers which is
different from predicting missing values for classification. Our imputation method uses an …

Beyond existing multi-view clustering, this paper studies a more realistic clustering scenario,
referred to as incomplete multi-view clustering, where a number of data instances are …