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 "codes for updating linear functions over small fields"):
  Abstract: We consider a point-to-point communication scenario where the receiver maintains a specific linear function of a message vector over a finite field. When the value of the message vector undergoes a sparse update, the transmitter broadcasts a coded version of the modified message while the receiver uses this codeword and the current value of the linear function to update its contents. It is assumed that the transmitter has access to the modified message but is unaware of the exact difference vector between the original and modified messages. Under the assumption that the difference vector is sparse and that its Hamming weight is at the most a known constant, the objective is to design a linear code with as small a codelength as possible that allows successful update of the linear function at the receiver. This problem is motivated by applications to distributed data storage systems. Recently, Prakash and Medard derived a lower bound on the codelength, which is independent of the size of the underlying finite field, and provided constructions that achieve this bound if the size of the finite field is sufficiently large. However, this requirement on the field size can be prohibitive for even moderate values of the system parameters. In this paper, we provide a field-size aware analysis of the function update problem, including a tighter lower bound on the codelength, and design codes that trade-off the codelength for a smaller field size requirement. We first characterize the family of function update problems where linear coding can provide reduction in codelength compared to a naive transmission scheme. We then provide field-size dependent bounds on the optimal codelength, and construct coding schemes when the receiver maintains linear functions of striped message vector. Finally, we show that every function update problem is equivalent to a generalized index coding problem.

Includes members:
  Member "updating content in cache aided coded multicast":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "the role of caching in future communication systems and networks")
  Member "multi version coding for consistent distributed storage of correlated data updates":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "harnessing correlations in distributed erasure coded key value stores")
  Member "communication cost for updating linear functions when message updates are sparse connections to maximally recoverable codes":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "harnessing correlations in distributed erasure coded key value stores")
  Member "vector network coding based on subspace codes outperforms scalar linear network coding":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "roos bound for skew cyclic codes in hamming and rank metric")
  Member "error correcting functional index codes generalized exclusive laws and graph coloring":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "code equivalences between network codes with link errors and index codes with side information errors")
  Member "multi version coding an information theoretic perspective of consistent distributed storage":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "convertible codes efficient conversion of coded data in distributed storage")
  Member "index coding with coded side information":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "code equivalences between network codes with link errors and index codes with side information errors")
  Member "fundamental limits on communication for oblivious updates in storage networks":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "harnessing correlations in distributed erasure coded key value stores")

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)