.png){kind=icon}
Return
SCAE: Structural Contrastive Auto-Encoder for Incomplete Multi-View Representation Learning
.png){kind=icon}
OA
AI
DOI：10.1145/3672078.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Describing an object from multiple perspectives often leads to incomplete data representation. Consequently, learning consistent representations for missing data from multiple views has emerged as a key focus in the realm of Incomplete Multi-view Representation Learning (IMRL). In recent years, various strategies, such as subspace learning, matrix decomposition, and deep learning, have been harnessed to develop numerous IMRL methods. In this article, our primary research revolves around IMRL, with a particular emphasis on addressing two main challenges. Firstly, we delve into the effective integration of intra-view similarity and contextual structure into a unified framework. Secondly, we explore the effective facilitation of information exchange and fusion across multiple views. To tackle these issues, we propose a deep learning approach known as Structural Contrastive Auto-Encoder (SCAE) to solve the challenges of IMRL. SCAE comprises two major components: intra-view structural representation learning and inter-view contrastive representation learning. The former involves capturing intra-view similarity by minimizing the Dirichlet energy of the feature matrix, while also applying spatial dispersion regularization to capture intra-view contextual structure. The latter encourages maximizing the mutual information of inter-view representations, facilitating information exchange and fusion across views. Experimental results demonstrate the efficacy of our approach in significantly enhancing model accuracy and robustly addressing IMRL problems. The code is available at https://github.com/limengran98/SCAE.
Keywords:
Incomplete multi-view representation learning
MC-VAE
Dirichlet energy
mutual information maximization
contrastive learning
Journal
IF:
6
Papers:
2.0K
Citations:
5.4K
Organization
Cited Papers
An Increased Lateral Femoral Condyle Ratio Is a Risk Factor for Anterior Cruciate Ligament Injury
PREAI
ShareSaveShareSaveOC-080 Ibd-Sshamp (Supported, Self help and Management Programme); UK’S first Internet based Remote Management System for Managing Stable IBD.png)
Gut
OAAI
GutIF0
OAAIShareSaveShareSaveElastic band structures of two-dimensional solid phononic crystal with negative Poisson's ratios
PREAI
ShareSave
View more