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: "on the capacity of non coherent network coding"
  Abstract: We consider the problem of multicasting information from a source to a set of receivers over a network where intermediate network nodes perform randomized network coding operations on the source packets. We propose a channel model for the non-coherent network coding introduced by Koetter and Kschischang in [6], that captures the essence of such a network operation, and calculate the capacity as a function of network parameters. We prove that use of subspace coding is optimal, and show that, in some cases, the capacity-achieving distribution uses subspaces of several dimensions, where the employed dimensions depend on the packet length. This model and the results also allow us to give guidelines on when subspace coding is beneficial for the proposed model and by how much, in comparison to a coding vector approach, from a capacity viewpoint. We extend our results to the case of multiple source multicast that creates a virtual multiple access channel.

Connected through hyperedge HE-1 (induced by source paper "batched sparse codes"):
  with members:
    - "overhead optimized gamma network codes"
    - "effects of the generation size and overlap on throughput and complexity in randomized linear network coding"
    - "coding for linear operator channels over finite fields"
    - "communication over finite field matrix channels"
    - "overlapped chunked network coding"
    - "sparse network coding with overlapping classes"
    - "compute and forward harnessing interference through structured codes"
    - "packing and covering properties of subspace codes for error control in random linear network coding"

Connected through hyperedge HE-2 (induced by source paper "on multiplicative matrix channels over finite chain rings"):
  with members:
    - "communication over finite chain ring matrix channels"
    - "an algebraic approach to physical layer network coding"
    - "on the capacity of multiplicative finite field matrix channels"
    - "universal secure network coding via rank metric codes"
    - "physical layer network coding tutorial survey and beyond"
    - "coding for linear operator channels over finite fields"
    - "communication over finite field matrix channels"
    - "compute and forward harnessing interference through structured codes"

Connected through hyperedge HE-3 (induced by source paper "an upper bound on broadcast subspace codes"):
  with members:
    - "the capacity of random linear coding networks as subspace channels"
    - "coding for linear operator channels over finite fields"
    - "multishot codes for network coding using rank metric codes"
    - "communication over finite field matrix channels"
    - "towards the capacity region of multiplicative linear operator broadcast channels"
    - "multishot codes for network coding bounds and a multilevel construction"
    - "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 "towards the capacity region of multiplicative linear operator broadcast channels"):
  with members:
    - "the capacity of random linear coding networks as subspace channels"
    - "recursive code construction for random networks"
    - "coding for linear operator channels over finite fields"
    - "communication over finite field matrix channels"
    - "multishot codes for network coding bounds and a multilevel construction"
    - "projective space codes for the injection metric"
    - "error correcting codes in projective spaces via rank metric codes and ferrers diagrams"
    - "a rank metric approach to error control in random network coding"

Connected through hyperedge HE-5 (induced by source paper "coding for linear operator channels over finite fields"):
  with members:
    - "communication over finite field matrix channels"
    - "combinatiorial algorithms for wireless information flow"
    - "multishot codes for network coding bounds and a multilevel construction"
    - "a rank metric approach to error control in random network coding"
    - "network coding for distributed storage systems"
    - "coding for errors and erasures in random network coding"
    - "coding for network coding"
    - "wireless network information flow"

Connected through hyperedge HE-6 (induced by source paper "the capacity of random linear coding networks as subspace channels"):
  with members:
    - "multishot codes for network coding using rank metric codes"
    - "fast encoding and decoding of gabidulin codes"
    - "multishot codes for network coding bounds and a multilevel construction"
    - "a rank metric approach to error control in random network coding"
    - "coding for errors and erasures in random network coding"
    - "coding for network coding"

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)