MemMap: An Adaptive and Latent Memory Structure for Dynamic Graph Learning
Abstract
Supplemental Material
- Download
- 20.69 MB
References
Index Terms
- MemMap: An Adaptive and Latent Memory Structure for Dynamic Graph Learning
Recommendations
Latent Features Embedded Dynamic Graph Evolution Deep Clustering Network
Highlights- We propose a dynamic graph evolution deep clustering network;
- A dynamic graph ...
AbstractAs a typical unsupervised machine learning task, clustering is always a hot research topic. Motivated by deep learning approaches, deep clustering has become prevalent in recent years, and achieves appealing performance. Most of ...
Towards Time-Variant-Aware Link Prediction in Dynamic Graph Through Self-supervised Learning
Advanced Data Mining and ApplicationsAbstractDynamic graph link prediction is a challenging problem because the graph topology and node attributes vary at different times. A purely supervised learning scheme for the dynamic graph data usually leads to poor generalization due to insufficient ...
Unsupervised multi-view feature extraction with dynamic graph learning
Highlights- We devise a framework that unifies dynamic graph and feature extraction learning.
- An effective optimization solution guaranteed desirable convergence is proposed.
- Extensive experiments on public multi-view datasets demonstrate the ...
AbstractGraph-based multi-view feature extraction has attracted much attention in literature. However, conventional solutions generally rely on a manually defined affinity graph matrix, which is hard to capture the intrinsic sample relations in multiple ...
Comments
Information & Contributors
Information
Published In
Sponsors
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Check for updates
Author Tags
Qualifiers
- Research-article
Funding Sources
- the National Natural Science Foundation of China
- the Fundamental Research Funds for the Central Universities
Conference
Acceptance Rates
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 162Total Downloads
- Downloads (Last 12 months)162
- Downloads (Last 6 weeks)162
Other Metrics
Citations
View Options
Get Access
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in