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: "compress and forward scheme for relay networks backword decoding and connection to bisubmodular flows"
  Abstract: In this paper, a compress-and-forward scheme with backward decoding is presented for the unicast wireless relay network. The encoding at the source and relay is a generalization of the noisy network coding scheme (NNC). While it achieves the same reliable data rate as noisy network coding scheme, the backward decoding allows for a better decoding complexity as compared to the joint decoding of the NNC scheme. Characterizing the layered decoding scheme is shown to be equivalent to characterizing an information flow for the wireless network. A node-flow for a graph with bisubmodular capacity constraints is presented and a max-flow min-cut theorem is proved for it. This generalizes many well-known results of flows over capacity constrained graphs studied in computer science literature. The results for the unicast relay network are generalized to the network with multiple sources with independent messages intended for a single destination.

Connected through hyperedge HE-1 (induced by source paper "capacity approximations for gaussian relay networks"):
  with members:
    - "improved capacity approximations for gaussian relay networks"
    - "achieving the capacity of the n relay gaussian diamond network within log n bits"
    - "wireless network information flow a deterministic approach"
    - "computation alignment capacity approximation without noise accumulation"
    - "short message quantize forward network coding"
    - "on the optimal compressions in the compress and forward relay schemes"
    - "ergodic interference alignment"
    - "compute and forward harnessing interference through structured codes"

Connected through hyperedge HE-2 (induced by source paper "short message noisy network coding with a decode forward option"):
  with members:
    - "mixed noisy network coding and cooperative unicasting in wireless networks"
    - "a unified relay framework with both d f and c f relay nodes"
    - "wireless network information flow a deterministic approach"
    - "on compress forward without wyner ziv binning for relay networks"
    - "short message quantize forward network coding"
    - "slepian wolf coding over cooperative relay networks"
    - "on the optimal compressions in the compress and forward relay schemes"
    - "noisy network coding"

Connected through hyperedge HE-3 (induced by source paper "a unified relay framework with both d f and c f relay nodes"):
  with members:
    - "selective coding strategy for unicast composite networks"
    - "wireless network information flow a deterministic approach"
    - "short message quantize forward network coding"
    - "on the optimal compressions in the compress and forward relay schemes"
    - "noisy network coding"
    - "lecture notes on network information theory"
    - "an improvement of cover el gamal s compress and forward relay scheme"
    - "analysis of a mixed strategy for multiple relay networks"

Connected through hyperedge HE-4 (induced by source paper "multicommodity flows and cuts in polymatroidal networks"):
  with members:
    - "capacity of multiple unicast in wireless networks a polymatroidal approach"
    - "wireless network information flow a deterministic approach"
    - "approximation algorithms for submodular multiway partition"
    - "submodular cost allocation problem and applications"
    - "submodular functions extensions distributions and algorithms a survey"

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)