Human Collective Intelligence Inspired Multi-View Representation Learning — Enabling View Communication by Simulating Human Communication Mechanism

Author:

Jia Xiaodong1ORCID,Jing Xiao-Yuan1ORCID,Sun Qixing1,Chen Songcan2ORCID,Du Bo1ORCID,Zhang David3ORCID

Affiliation:

1. Hubei Key Laboratory of Multimedia and Network Communication Engineering, School of Computer Science, National Engineering Research Center for Multimedia Software, Institute of Artificial Intelligence, Wuhan University, Wuhan, Hubei, China

2. College of Computer Science and Technology / MIIT Key Laboratory of Pattern Analysis & Machine Intelligence, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu, China

3. School of Data Science, The Chinese University of Hong Kong, Shenzhen, Guangdong, China

Funder

NSFC

Innovation Group of Guangdong Education Department

2019 Key Discipline project of Guangdong Province

State Key Laboratory for Novel Software Technology

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Applied Mathematics,Artificial Intelligence,Computational Theory and Mathematics,Computer Vision and Pattern Recognition,Software

Reference87 articles.

1. On deep multi-view representation learning;wang;Proc Int Conf Mach Learn,0

2. A Survey on Multi-Task Learning

3. Multimodal learning with deep boltzmann machines;srivastava;Proc Conf Neural Inf Process Syst,2012

4. Facial Landmark Detection by Deep Multi-task Learning

5. Deep multi-view representation learning for multi-modal features of the schizophrenia and schizo-affective disorder

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