Multi-view representation learning aims to derive robust representations that are both view-
consistent and view-specific from diverse data sources. This paper presents an in-depth …

Graph convolutional network has shown excellent performance in multi-view classification.
Currently, to output a fused node embedding representation in multi-view scenarios, existing …

The challenges posed by heterogeneous data in practical applications have made multiview
semi-supervised classification a focus of attention for researchers. While several graph …

Unlike traditional supervised classification, complementary label learning (CLL) operates
under a weak supervision framework, where each sample is annotated by excluding several …

The design of effective multi-view clustering algorithms has recently garnered significant
research attention. In this paper, we develop a robust multi-view clustering via collaborative …

Various knowledge distillation (KD) methods for recommender systems have been recently
introduced to achieve two goals:(i) obtaining an inference time shorter than the cumbersome …