Online learning of Hawkes processes has received increasing attention in the last couple of years especially for modeling a network of actors. However, these works typically either model the rich interaction between the events or the latent cluster of the actors or the network structure between the actors. We propose to model the latent structure of the network of actors as well as their rich interaction across events for real-world settings of medical and financial applications. Experimental results on both synthetic and real-world data showcase the efficacy of our approach.

翻译：过去几年来,对霍克斯进程的在线学习越来越受到关注,特别是模拟一个行为者网络,然而,这些工作通常要么模拟事件之间的丰富互动,要么模拟行为者的潜在集群,要么模拟行为者之间的网络结构。 我们提议模拟行为者网络的潜在结构,以及行为者在现实世界的医疗和金融应用环境中的各种事件之间的丰富互动。合成数据和现实世界数据的实验结果显示了我们的方法的有效性。