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 "error correction for index coding with coded side information"):
  Abstract: Index coding is a source coding problem in which a broadcaster seeks to meet the different demands of several users, each of whom is assumed to have some prior information on the data held by the sender. If the sender knows its clients' requests and their side-information sets, then the number of packet transmissions required to satisfy all users' demands can be greatly reduced if the data is encoded before sending. The collection of side-information indices as well as the indices of the requested data is described as an instance of the index coding with side-information (ICSI) problem. The encoding function is called the index code of the instance, and the number of transmissions employed by the code is referred to as its length. The main ICSI problem is to determine the optimal length of an index code for and instance. As this number is hard to compute, bounds approximating it are sought, as are algorithms to compute efficient index codes. Two interesting generalizations of the problem that have appeared in the literature are the subject of this work. The first of these is the case of index coding with coded side information, in which linear combinations of the source data are both requested by and held as users' side-information. The second is the introduction of error-correction in the problem, in which the broadcast channel is subject to noise. #R##N#In this paper we characterize the optimal length of a scalar or vector linear index code with coded side information (ICCSI) over a finite field in terms of a generalized min-rank and give bounds on this number based on constructions of random codes for an arbitrary instance. We furthermore consider the length of an optimal error correcting code for an instance of the ICCSI problem and obtain bounds on this number, both for the Hamming metric and for rank-metric errors. We describe decoding algorithms for both categories of errors.

Includes members:
  Member "bounding the optimal rate of the icsi and iccsi problem":
    also connected through other hyperedges:
      (none)
  Member "on the optimality of uncoded cache placement":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "fundamental limits of wireless caching under mixed cacheable and uncacheable traffic")
  Member "structural properties of index coding capacity using fractional graph theory":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "cooperative multi sender index coding")
  Member "index coding and network coding via rank minimization":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "subspace aware index codes")
  Member "graph theory versus minimum rank for index coding":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "embedded index coding")
  Member "fundamental limits of caching improved bounds for small buffer users":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "an index coding approach to caching with uncoded cache placement")
  Member "fundamental limits of caching":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "fundamental limits of wireless caching under mixed cacheable and uncacheable traffic")
  Member "an equivalence between network coding and index coding":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "embedded index coding")

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)