首页|Researchers from Shenzhen University Describe Findings in Computational Intellig ence (Possibilistic Neighborhood Graph: a New Concept of Similarity Graph Learning)
Researchers from Shenzhen University Describe Findings in Computational Intellig ence (Possibilistic Neighborhood Graph: a New Concept of Similarity Graph Learning)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Data detailed on Machine Learning - Co mputational Intelligence have been presented. According to news reporting origin ating in Shenzhen, People’s Republic of China, by NewsRx journalists, research s tated, “Adaptive graph-based representation and learning methods have received e xtensive attention due to their good performance in supervised and unsupervised learning tasks. These methods often involve probability constraint, i.e., the su m-to-one constraint, when learning a similarity graph.” Funders for this research include Guangdong Basic and Applied Basic Research Fou ndation, National Natural Science Foundation of China (NSFC), Shenzhen Science and Technology Program, Natural Science Key Foundation of Jiangsu Education Depar tment.
ShenzhenPeople’s Republic of ChinaAsiaComputational IntelligenceEmerging TechnologiesGraph LearningMachine L earningShenzhen University
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