A Point Process Model for Optimizing Repeated Personalized Action Delivery to Users
arXiv:2501.02961v1h-index: 1
Originality Synthesis-oriented
AI Analysis
This work addresses causal inference challenges in user-advertiser interactions, offering a domain-specific approach that appears incremental in its method development.
The paper tackles the problem of optimizing repeated personalized actions for users, such as in online advertising, by introducing a formalism based on temporal marked point processes and proposing neural point processes as practical solutions.
This paper provides a formalism for an important class of causal inference problems inspired by user-advertiser interaction in online advertiser. Then this formalism is specialized to an extension of temporal marked point processes and the neural point processes are suggested as practical solutions to some interesting special cases.