Skip to content
conftrace_
2019 IJCAI IJCAI 2019

Unsupervised Multi-view Learning

Abstract

Unsupervised multi-view learning is a hot research topic. The main challenge lies in how to integrate information from different views to enhance the unsupervised learning performance. In this paper, we present our research works on multi-view data clustering and multi-view network community detection respectively. The main contributions are summarized by emphasizing the challenges we have addressed. In addition, the ongoing work and the future work are briefly presented.

🐣 Hot Topic Early Bird - multi-view clustering

Authors

Ling Huang

Topics

Machine Learning > Core Methods > Clustering Machine Learning > Learning Types > Unsupervised Learning

Keywords

multi-view clustering unsupervised learning community detection view integration
Download PDF

More from IJCAI 2019

All IJCAI 2019 papers →
Vision beyond Pixels: Visual Reasoning via Blocksworld Abstractions
A Unified Mathematical Approach for Foraging and Construction Systems in a 1,000,000 Robot Swarm
Can Meta-Interpretive Learning outperform Deep Reinforcement Learning of Evaluable Game strategies?
Intelligent Agent for Assessing and Guiding Rehabilitation Exercises
Optimizing Interactive Systems with Data-Driven Objectives
Split Q Learning: Reinforcement Learning with Two-Stream Rewards