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 …

Accurate perception of the performance degradation of fuel cell is very important to detect its
health state. However, inconsistent operating conditions of fuel cell vehicles in the test result …

Multi-view anchor graph clustering selects representative anchors to avoid full pair-wise
similarities and therefore reduce the complexity of graph methods. Although widely applied …

As a leading graph clustering technique, spectral clustering is one of the most widely used
clustering methods to capture complex clusters in data. Some additional prior information …

Clustering categorical data is an important task of machine learning, since the type of data
widely exists in real world. However, the lack of an inherent order on the domains of …

As a leading graph clustering technique, spectral clustering is one of the most widely used
clustering methods that captures complex clusters in data. However, some of its deficiencies …

Consensus clustering can derive a more promising and robust clustering result by
integrating multiple partitions strategically. However, there are several limitations in the …

Accurate clustering is a challenging task with unlabeled data. Ensemble clustering aims to
combine sets of base clusterings to obtain a better and more stable clustering and has …

Spectral clustering, one of the most popular clustering methods, has attracted considerable
attention in many fields owing to its excellent empirical properties. However, previously …

This study seeks to develop a better understanding of the thrust allocation process of over-
actuated marine vessels. A two-stage analysis framework is proposed for thrust allocation …