首页|Shenzhen University Details Findings in Computational Intelligence (Influence Ma ximization In Complex Networks By Using Evolutionary Deep Reinforcement Learning )
Shenzhen University Details Findings in Computational Intelligence (Influence Ma ximization In Complex Networks By Using Evolutionary Deep Reinforcement Learning )
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Research findings on Machine Learning - Computati onal Intelligence are discussed in a new report. According to news reporting fro m Shenzhen, People’s Republic of China, by NewsRx journalists, research stated, “Influence maximization (IM) in complex networks tries to activate a small subse t of seed nodes that could maximize the propagation of influence. The studies on IM have attracted much attention due to their wide applications such as item re commendation, viral marketing, information propagation and disease immunization. ”
ShenzhenPeople’s Republic of ChinaAsiaComputational IntelligenceAlgorithmsEmerging TechnologiesMachine LearningReinforcement LearningShenzhen University
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