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Online Continuous-Time Tensor Factorization Based on Pairwise Interactive Point Processes
2018
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence
A continuous-time tensor factorization method is developed for event sequences containing multiple "modalities." Each data element is a point in a tensor, whose dimensions are associated with the discrete alphabet of the modalities. Each tensor data element has an associated time of occurence and a feature vector. We model such data based on pairwise interactive point processes, and the proposed framework connects pairwise tensor factorization with a feature-embedded point process. The model
doi:10.24963/ijcai.2018/403
dblp:conf/ijcai/XuLC18
fatcat:3mrtbkczi5ejnchaxkk2vcwsdi