  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.
