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 "bounds on separating redundancy of linear codes and rates of x codes"):
  Abstract: An error-erasure channel is a simple noise model that introduces both errors and erasures. While the two types of errors can be corrected simultaneously with error-correcting codes, it is also known that any linear code allows for first correcting errors and then erasures in two-step decoding. In particular, a carefully designed parity-check matrix not only allows for separating erasures from errors but also makes it possible to efficiently correct erasures. The separating redundancy of a linear code is the number of parity-check equations in a smallest parity-check matrix that has the required property for this error-erasure separation. In a sense, it is a parameter of a linear code that represents the minimum overhead for efficiently separating erasures from errors. While several bounds on separating redundancy are known, there still remains a wide gap between upper and lower bounds except for a few limited cases. In this paper, using probabilistic combinatorics and design theory, we improve both upper and lower bounds on separating redundancy. We also show a relation between parity-check matrices for error-erasure separation and special matrices, called X-codes, for data compaction circuits in VLSI testing. This leads to an exponentially improved bound on the size of an optimal X-code.

Includes members:
  Member "probabilistic bounds on the trapping redundancy of linear codes":
    also connected through other hyperedges:
      (none)
  Member "on generic erasure correcting sets and related problems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "stopping sets of algebraic geometry codes")
  Member "a combinatorial approach to x tolerant compaction circuits":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "on the maximum number of codewords of x codes of constant weight three")
  Member "the trapping redundancy of linear block codes":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "performance bounds and estimates for quantized ldpc decoders")
  Member "on parity check collections for iterative erasure decoding that correct all correctable erasure patterns of a given size":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "stopping redundancy hierarchy beyond the minimum distance")
  Member "results on parity check matrices with optimal stopping and or dead end set enumerators":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "stopping set distributions of some linear codes")
  Member "on the stopping distance and the stopping redundancy of codes":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "decoder tailored polar code design using the genetic algorithm")
  Member "improved upper bounds on stopping redundancy":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "stopping redundancy hierarchy beyond the minimum distance")

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)