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: "multiple access network information flow and correction codes"
  Abstract: This work considers the multiple-access multicast error-correction scenario over a packetized network with z malicious edge adversaries. The network has min-cut m and packets of length l, and each sink demands all information from the set of sources S. The capacity region is characterized for both a “side-channel” model (where sources and sinks share some random bits that are secret from the adversary) and an “omniscient” adversarial model (where no limitations on the adversary's knowledge are assumed). In the “side-channel” adversarial model, the use of a secret channel allows higher rates to be achieved compared to the “omniscient” adversarial model, and a polynomial-complexity capacity-achieving code is provided. For the “omniscient” adversarial model, two capacity-achieving constructions are given: the first is based on random subspace code design and has complexity exponential in lm, while the second uses a novel multiple-field-extension technique and has O(lm|S|) complexity, which is polynomial in the network size. Our code constructions are “end-to-end” in that all nodes except the sources and sinks are oblivious to the adversaries and may simply implement predesigned linear network codes (random or otherwise). Also, the sources act independently without knowledge of the data from other sources.

Connected through hyperedge HE-1 (induced by source paper "adversarial network coding"):
  with members:
    - "equivalence for networks with adversarial state"
    - "polytope codes against adversaries in networks"
    - "on metrics for error correction in network coding"
    - "adversarial models and resilient schemes for network coding"
    - "a rank metric approach to error control in random network coding"
    - "coding for errors and erasures in random network coding"
    - "construction algorithm for network error correcting codes attaining the singleton bound"

Connected through hyperedge HE-2 (induced by source paper "coding with constraints minimum distance bounds and systematic constructions"):
  with members:
    - "storage capacity of repairable networks"
    - "optimal locally repairable and secure codes for distributed storage systems"
    - "a family of optimal locally recoverable codes"
    - "on the existence of mds codes over small fields with constrained generator matrices"
    - "balanced sparsest generator matrices for mds codes"
    - "optimal locally repairable codes and connections to matroid theory"
    - "codes with local regeneration"
    - "optimal linear codes with a local error correction property"

Connected through hyperedge HE-3 (induced by source paper "weakly secure mds codes for simple multiple access networks"):
  with members:
    - "on the existence of mds codes over small fields with constrained generator matrices"
    - "balanced sparsest generator matrices for mds codes"
    - "on block security of regenerating codes at the mbr point for distributed storage systems"

Connected through hyperedge HE-4 (induced by source paper "efficient and universal corruption resilient fountain codes"):
  with members:
    - "fast encoding and decoding of gabidulin codes"
    - "coding for errors and erasures in random 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)