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 "audience retention rate aware caching and coded video delivery with asynchronous demands"):
  Abstract: Most results on coded caching focus on a static scenario, in which a fixed number of users synchronously place their requests from a content library, and the performance is measured in terms of the latency in satisfying all of these demands. In practice, however, users start watching an online video content asynchronously over time, and often abort watching a video before it is completed. The latter behaviour is captured by the notion of audience retention rate, which measures the portion of a video content watched on average. In order to bring coded caching one step closer to practice, asynchronous user demands are considered in this paper, by allowing user demands to arrive randomly over time, and both the popularity of video files, and the audience retention rates are taken into account. A decentralized partial coded caching (PCC) scheme is proposed, together with two cache allocation schemes; namely the optimal cache allocation (OCA) and the popularity-based cache allocation (PCA), which allocate users' caches among different chunks of the video files in the library. Numerical results validate that the proposed PCC scheme, either with OCA or PCA, outperforms conventional uncoded caching as well as the state-of-the-art decentralized caching schemes, which consider only the file popularities, and are designed for synchronous demand arrivals. An information-theoretical lower bound on the average delivery rate is also presented.

Includes members:
  Member "asynchronous coded caching":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "decentralized asynchronous coded caching design and performance analysis in fog radio access networks")
  Member "a reinforcement learning approach to proactive caching in wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "online convex optimization for caching networks")
  Member "coded caching and content delivery with heterogeneous distortion requirements":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "content caching and delivery in wireless radio access networks")
  Member "coded caching for a large number of users":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "an index coding approach to caching with uncoded cache placement")
  Member "wireless content caching for small cell and d2d networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a unified framework for constructing centralized coded caching schemes")
  Member "decentralized caching and coded delivery with distinct cache capacities":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "content caching and delivery in wireless radio access networks")
  Member "order optimal rate of caching and coded multicasting with random demands":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "an index coding approach to caching with uncoded cache placement")
  Member "adapting caching to audience retention rate which video chunk to store":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "learning to cache with no regrets")

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)