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 learning based approach to caching in heterogenous small cell networks"):
  Abstract: A heterogenous network with base stations (BSs), small base stations (SBSs), and users distributed according to independent Poisson point processes is considered. SBS nodes are assumed to possess high storage capacity and to form a distributed caching network. Popular files are stored in local caches of SBSs, so that a user can download the desired files from one of the SBSs in its vicinity. The offloading-loss is captured via a cost function that depends on the random caching strategy proposed here. The popularity profile of cached content is unknown and estimated using instantaneous demands from users within a specified time interval. An estimate of the cost function is obtained from which an optimal random caching strategy is devised. The training time to achieve an   $\epsilon > 0$   difference between the achieved and optimal costs is finite provided the user density is greater than a predefined threshold, and scales as   $N^2$  , where   $N$   is the support of the popularity profile. A transfer learning-based approach to improve this estimate is proposed. The training time is reduced when the popularity profile is modeled using a parametric family of distributions; the delay is independent of   $N$   and scales linearly with the dimension of the distribution parameter.

Includes members:
  Member "caching with unknown popularity profiles in small cell networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "analysis and optimization of caching and multicasting in large scale cache enabled heterogeneous wireless networks")
  Member "analysis on cache enabled wireless heterogeneous networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "reinforcement learning based cooperative coded caching under dynamic popularities in ultra dense networks")
  Member "a transfer learning approach for cache enabled wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a survey on machine learning based performance improvement of wireless networks phy mac and network layer")
  Member "efficient scheduling and power allocation for d2d assisted wireless caching networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "individual preference aware caching policy design in wireless d2d networks")
  Member "modeling and analysis of content caching in wireless small cell networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "enhancing physical layer security of random caching in large scale multi antenna heterogeneous wireless networks")
  Member "hierarchical coded caching":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "subexponential and linear subpacketization coded caching via line graphs and projective geometry")
  Member "mobicacher mobility aware content caching in small cell networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "optimal scheduling of content caching subject to deadline")
  Member "learning based optimization of cache content in a small cell base station":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "optimal scheduling of content caching subject to deadline")

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)