human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "fake news mitigation via point process based intervention"):
  Abstract: We propose the first multistage intervention framework that tackles fake news in social networks by combining reinforcement learning with a point process network activity model. The spread of fake news and mitigation events within the network is modeled by a multivariate Hawkes process with additional exogenous control terms. By choosing a feature representation of states, defining mitigation actions and constructing reward functions to measure the effectiveness of mitigation activities, we map the problem of fake news mitigation into the reinforcement learning framework. We develop a policy iteration method unique to the multivariate networked point process, with the goal of optimizing the actions for maximal total reward under budget constraints. Our method shows promising performance in real-time intervention experiments on a Twitter network to mitigate a surrogate fake news campaign, and outperforms alternatives on synthetic datasets.

Includes members:
  Member "recurrent poisson factorization for temporal recommendation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a collaborative filtering model with heterogeneous neural networks for recommender systems")
  Member "distilling information reliability and source trustworthiness from digital traces":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "intensity free learning of temporal point processes")
  Member "wasserstein learning of deep generative point process models":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "transformer hawkes process")
  Member "multistage campaigning in social networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "meta learning with relational information for short sequences")
  Member "steering opinion dynamics in information diffusion networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "the mass fake news and cognition security")
  Member "detecting weak changes in dynamic events over networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "fast change point detection on dynamic social networks")
  Member "learning granger causality for hawkes processes":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "learning multivariate hawkes processes at scale")
  Member "smart broadcasting do you want to be seen":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "can a user guess what her followers want")

Question: Please tell me which class the source paper belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.LG(Machine Learning)