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 "an index coding approach to caching with uncoded cache placement"):
  Abstract: Caching is an efficient way to reduce network traffic congestion during peak hours, by storing some content at the user's local cache memory, even without knowledge of user's later demands. Maddah-Ali and Niesen proposed a two-phase (placement phase and delivery phase) coded caching strategy for broadcast channels with cache-aided users. This paper investigates the same model under the constraint that content is placed uncoded within the caches, that is, when bits of the files are simply copied within the caches. When the cache contents are uncoded and the users' demands are revealed, the caching problem can be connected to an index coding problem. This paper focuses on deriving fundamental performance limits for the caching problem by using tools for the index coding problem that were either known or are newly developed in this work. First, a converse bound for the caching problem under the constraint of uncoded cache placement is proposed based on the "acyclic index coding converse bound". This converse bound is proved to be achievable by the Maddah-Ali and Niesen's scheme when the number of files is not less than the number of users, and by a newly derived index coding achievable scheme otherwise. The proposed index coding achievable scheme is based on distributed source coding and strictly improves on the widely used "composite (index) coding" achievable bound and its improvements, and is of independent interest. An important consequence of the findings of this paper is that advancements on the coded caching problem posed by Maddah-Ali and Niesen are thus only possible by considering strategies with coded placement phase. A recent work by Yu et al. has however shown that coded cache placement can at most half the network load compared to the results presented in this paper.

Includes members:
  Member "on the optimality of d2d coded caching with uncoded cache placement and one shot delivery":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on optimal load memory tradeoff of cache aided scalar linear function retrieval")
  Member "the exact rate memory tradeoff for caching with uncoded prefetching":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "fundamental limits of wireless caching under mixed cacheable and uncacheable traffic")
  Member "coded caching with shared caches fundamental limits with uncoded prefetching":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "rate memory trade off for multi access coded caching with uncoded placement")
  Member "benefits of cache assignment on degraded broadcast channels":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "fundamental limits of wireless caching under mixed cacheable and uncacheable traffic")
  Member "characterizing the rate memory tradeoff in cache networks within a factor of 2":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "fundamental limits of wireless caching under mixed cacheable and uncacheable traffic")
  Member "improved converses and gap results for coded caching":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "rate memory trade off for multi access coded caching with uncoded placement")
  Member "on the capacity for distributed index coding":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "cooperative multi sender index coding")
  Member "coded caching for a large number of users":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "the exact rate memory tradeoff for caching with uncoded prefetching")

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)