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 "a hybrid model based and data driven approach to spectrum sharing in mmwave cellular networks"):
  Abstract: Inter-operator spectrum sharing in millimeter-wave bands has the potential of substantially increasing the spectrum utilization and providing a larger bandwidth to individual user equipment at the expense of increasing inter-operator interference. Unfortunately, traditional model-based spectrum sharing schemes make idealistic assumptions about inter-operator coordination mechanisms in terms of latency and protocol overhead, while being sensitive to missing channel state information. In this paper, we propose hybrid model-based and data-driven multi-operator spectrum sharing mechanisms, which incorporate model-based beamforming and user association complemented by data-driven model refinements. Our solution has the same computational complexity as a model-based approach but has the major advantage of having substantially less signaling overhead. We discuss how limited channel state information and quantized codebook-based beamforming affect the learning and the spectrum sharing performance. We show that the proposed hybrid sharing scheme significantly improves spectrum utilization under realistic assumptions on inter-operator coordination and channel state information acquisition.

Includes members:
  Member "how to escape saddle points efficiently":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "understanding global loss landscape of one hidden layer relu neural networks")
  Member "modeling infrastructure sharing in mmwave networks with shared spectrum licenses":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a brief history on the theoretical analysis of dense small cell wireless networks")
  Member "alternating minimization algorithms for hybrid precoding in millimeter wave mimo systems":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "beamforming design for large scale antenna arrays using deep learning")
  Member "subspace estimation and decomposition for large millimeter wave mimo systems":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "joint design of fronthauling and hybrid beamforming for downlink c ran systems")
  Member "spectrum sharing in mmwave cellular networks via cell association coordination and beamforming":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "machine learning for wireless communications in the internet of things a comprehensive survey")
  Member "sum rate maximization in sub 28 ghz millimeter wave mimo interfering networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "low overhead coordination in sub 28 millimeter wave networks")
  Member "stochastic geometry modeling and analysis of multi tier millimeter wave cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "impact of spatial multiplexing on throughput of ultra dense mmwave ap network")
  Member "the transitional behavior of interference in millimeter wave networks and its impact on medium access control":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "joint path selection and rate allocation framework for 5g self backhauled mm wave networks")

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.IT(Information Theory)