human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "hybrid noncoherent network coding"
  Abstract: We describe a novel extension of subspace codes for noncoherent networks, suitable for use when the network is viewed as a communication system that introduces both dimension and symbol errors. We show that when symbol erasures occur in a significantly large number of different basis vectors transmitted through the network and when the min-cut of the networks is much smaller then the length of the transmitted codewords, the new family of codes outperforms their subspace code counterparts. #R##N#For the proposed coding scheme, termed hybrid network coding, we derive two upper bounds on the size of the codes. These bounds represent a variation of the Singleton and of the sphere-packing bound. We show that a simple concatenated scheme that represents a combination of subspace codes and Reed-Solomon codes is asymptotically optimal with respect to the Singleton bound. Finally, we describe two efficient decoding algorithms for concatenated subspace codes that in certain cases have smaller complexity than subspace decoders.

Connected through hyperedge HE-1 (induced by source paper "reliable and secure multishot network coding using linearized reed solomon codes"):
  with members:
    - "skew and linearized reed solomon codes and maximum sum rank distance codes over any division ring"
    - "relative generalized matrix weights of matrix codes for universal security on wire tap networks"
    - "sub quadratic decoding of gabidulin codes"
    - "relative generalized rank weight of linear codes and its applications to network coding"
    - "convolutional codes in rank metric with application to random network coding"
    - "convolutional codes with maximum column sum rank for network streaming"
    - "bounds on list decoding of rank metric codes"
    - "universal secure network coding via rank metric codes"

Connected through hyperedge HE-2 (induced by source paper "symbol erasure correction capability of spread codes"):
  with members:
    - "message encoding and retrieval for spread and cyclic orbit codes"
    - "fast encoding and decoding of gabidulin codes"
    - "spread codes and spread decoding in network coding"
    - "coding for errors and erasures in random network coding"

Connected through hyperedge HE-3 (induced by source paper "end to end error correcting codes on networks with worst case symbol errors"):
  with members:
    - "binary error correcting network codes"
    - "on metrics for error correction in network coding"
    - "a rank metric approach to error control in random network coding"
    - "coding for errors and erasures in random network coding"

Connected through hyperedge HE-4 (induced by source paper "fulcrum network codes a code for fluid allocation of complexity"):
  with members:
    - "a survey on network codes for distributed storage"
    - "lightweight security for network coding"

Connected through hyperedge HE-5 (induced by source paper "problems on q analogs in coding theory"):
  with members:
    - "a complete characterization of irreducible cyclic orbit codes and their plucker embedding"
    - "new lower bounds for constant dimension codes"
    - "bounds for projective codes from semidefinite programming"
    - "cyclic orbit codes"
    - "list decoding of lifted gabidulin codes via the plucker embedding"
    - "isometry and automorphisms of constant dimension codes"
    - "list decoding subspace codes from insertions and deletions"
    - "decoding of subspace codes a problem of schubert calculus over finite fields"

Question: Please tell me which class the center node 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)