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 "intelligence stratum for iot architecture requirements and functions"):
  Abstract: The use of Artificial Intelligence (AI) is becoming increasingly pervasive and relevant in many different application areas. Researchers are putting a considerable effort to take full advantage of the power of AI, while trying to overcome the technical challenges that are intrinsically linked to almost any domain area of application, such as the Internet of Things (IoT). One of the biggest problems related to the use of AI in IoT is related to the difficulty of coping with the wide variety of protocols and software technologies used, as well as with the heterogeneity of the hardware resources consuming the AI. The scattered IoT landscape accentuates the limitations on interoperability, especially visible in the deployment of AI, affecting the seamless AI life-cycle management as well. In this paper, it is discussed how to enable AI distribution in IoT by introducing a layered intelligence architecture that aims to face the undertaken challenges taking into account the special requirements of nowadays IoT networks. It describes the main characteristics of the new paradigm architecture, highlighting what are the implications of its adoption from use cases perspective and their requirements. Finally, a set of open technical and research challenges are enumerated to reach the full potential of the intelligence distribution's vision.

Includes members:
  Member "distributing intelligence to the edge and beyond":
    also connected through other hyperedges:
      (none)
  Member "differentially private federated learning a client level perspective":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "trends and advancements in deep neural network communication")
  Member "going deeper with convolutions":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "discrimination aware network pruning for deep model compression")

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.CY(Computers and Society)