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: "noisy network coding with partial df"
  Abstract: In this paper, we propose a noisy network coding integrated with partial decode-and-forward relaying for single-source multicast discrete memoryless networks (DMN's). Our coding scheme generalizes the partial-decode-compress-and-forward scheme (Theorem 7) by Cover and El Gamal. This is the first time the theorem is generalized for DMN's such that each relay performs both partial decode-and-forward and compress-and-forward simultaneously. Our coding scheme simultaneously generalizes both noisy network coding by Lim, Kim, El Gamal, and Chung and distributed decode-and-forward by Lim, Kim, and Kim. It is not trivial to combine the two schemes because of inherent incompatibility in their encoding and decoding strategies. We solve this problem by sending the same long message over multiple blocks at the source and at the same time by letting the source find the auxiliary covering indices that carry information about the message simultaneously over all blocks.

Connected through hyperedge HE-1 (induced by source paper "an information theoretic analysis of the gaussian multicast channel with interactive user cooperation"):
  with members:
    - "enhancing multiuser mimo through opportunistic d2d cooperation"
    - "on the achievable rates of multihop virtual full duplex relay channels"
    - "a survey on device to device communication in cellular networks"
    - "massive mimo multicasting in noncooperative cellular networks"
    - "spectrum sharing for device to device communication in cellular networks"
    - "modeling analysis and optimization of multicast device to device transmissions"
    - "short message noisy network coding with rate splitting"
    - "half duplex or full duplex relaying a capacity analysis under self interference"

Connected through hyperedge HE-2 (induced by source paper "distributed decode forward for relay networks"):
  with members:
    - "partial decode forward relaying for the gaussian two hop relay network"
    - "optimized backhaul compression for uplink cloud radio access network"
    - "joint precoding and multivariate backhaul compression for the downlink of cloud radio access networks"
    - "index coding capacity how far can one go with only shannon inequalities"
    - "short message noisy network coding with a decode forward option"
    - "the approximate sum capacity of the symmetric gaussian k user interference channel"
    - "achieving the capacity of the n relay gaussian diamond network within log n bits"
    - "robust and efficient distributed compression for cloud radio access networks"

Connected through hyperedge HE-3 (induced by source paper "a unified approach for network information theory"):
  with members:
    - "short message noisy network coding with a decode forward option"
    - "hybrid coding an interface for joint source channel coding and network communication"
    - "simultaneous nonunique decoding is rate optimal"
    - "achievability proof via output statistics of random binning"
    - "wireless network information flow a deterministic approach"
    - "on the capacity of the noncausal relay channel"
    - "interference decoding for deterministic channels"
    - "slepian wolf coding over cooperative relay networks"

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)