Multi-view clustering has attracted increasing attention by reason of its ability to leverage the
complementarity of multi-view data. Existing multi-view clustering methods have explored …

Multi-view learning becomes increasingly attractive and promising because multimodal or
multi-view data are commonly encountered in real-world applications. In this study, we …

It is feasible to improve the performance of B-mode ultrasound (BUS) based computer-aided
diagnosis (CAD) for liver cancers by transferring knowledge from contrast-enhanced …

Multi-view learning aims to fully exploit the view-consistency and view-discrepancy for
performance improvement. Knowledge Distillation (KD), characterized by the so-called …

An effective method in machine learning often involves considerable experience with
algorithms and domain expertise. Many existing machine learning methods highly rely on …

Image classification is a critical and meaningful task in image retrieval, recognition and
object detection. In this paper, three-side efforts are taken to accomplish this task. First …

Cardiac indices estimation in multi-view images attracts great attention due to its capability
for cardiac function assessment. However, the variation of the cardiac indices across views …

Privileged information, a form of prior knowledge, can significantly enhance traditional
machine learning performance through a novel paradigm known as learning using …

Privileged information learning is proposed to construct the classifier by incorporating
privileged knowledge. At present, most of the privileged information learning methods …

Multi-view data has become fairly important since large amounts of information are
constantly generated from different sources. So far, most multi-view research on …