首页|New Machine Learning Findings from University of Sao Paulo Reported (Recovering Network Topology and Dynamics From Sequences: a Machine Learning Approach)
New Machine Learning Findings from University of Sao Paulo Reported (Recovering Network Topology and Dynamics From Sequences: a Machine Learning Approach)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Fresh data on Machine Learning are pre sented in a new report. According to newsreporting originating in Sao Carlos, B razil, by NewsRx journalists, research stated, “Sequences are prevalentin myria d real -world scenarios, making it imperative to discern the mechanisms behind s ymbol generationand, subsequently, to decode complex system behaviors. Divergin g from conventional graph analysismethods that primarily relies on Markov chain s and time series analysis, this paper offers a fresh perspectivebased on netwo rk science to understand sequences produced by agents navigating a networked top ology.”Financial supporters for this research include Conselho Nacional de Desenvolvime nto Cientifico e Tecnologico(CNPQ), Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP), Lilly Endowment,Inc., USA, Indiana University Pervasive Tec hnology Institute, USA.
Sao CarlosBrazilSouth AmericaCybor gsEmerging TechnologiesMachine LearningUniversity of Sao Paulo
NETL
NSTL
