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: "cut set bound is loose for gaussian relay networks"
  Abstract: The cut-set bound developed by Cover and El Gamal in 1979 has since remained the best known upper bound on the capacity of the Gaussian relay channel. We develop a new upper bound on the capacity of the Gaussian primitive relay channel which is tighter than the cut-set bound. Our proof is based on typicality arguments and concentration of Gaussian measure. Combined with a simple tensorization argument proposed by Courtade and Ozgur in 2015, our result also implies that the current capacity approximations for Gaussian relay networks, which have linear gap to the cut-set bound in the number of nodes, are order-optimal and leads to a lower bound on the pre-constant.

Connected through hyperedge HE-1 (induced by source paper "the arbitrarily varying relay channel"):
  with members:
    - "the capacity of the relay channel solution to cover s problem in the gaussian case"
    - "arbitrarily varying wiretap channels with type constrained states"
    - "the arbitrarily varying wiretap channel secret randomness stability and super activation"
    - "on the continuity of the secrecy capacity of compound and arbitrarily varying wiretap channels"
    - "capacity approximations for gaussian relay networks"
    - "the arbitrarily varying multiple access channel with conferencing encoders"
    - "secure communication over parallel relay channel"
    - "achieving the capacity of the n relay gaussian diamond network within log n bits"

Connected through hyperedge HE-2 (induced by source paper "capacity upper bounds for the relay channel via reverse hypercontractivity"):
  with members:
    - "the capacity of the relay channel solution to cover s problem in the gaussian case"
    - "brascamp lieb inequality and its reverse an information theoretic view"
    - "secret key generation with one communicator and a one shot converse via hypercontractivity"
    - "wasserstein continuity of entropy and outer bounds for interference channels"
    - "capacity of a class of modulo sum relay channels"

Connected through hyperedge HE-3 (induced by source paper "the arbitrarily varying gaussian relay channel with sender frequency division"):
  with members:
    - "the arbitrarily varying relay channel"
    - "a new coding paradigm for the primitive relay channel"
    - "arbitrarily varying wiretap channels with type constrained states"
    - "capacity approximations for gaussian relay networks"

Connected through hyperedge HE-4 (induced by source paper "wireless network simplification the performance of routing"):
  with members:
    - "network simplification in half duplex building on submodularity"
    - "network simplification for secure af relaying"
    - "consistency in the face of change an adaptive approach to physical layer cooperation"
    - "wireless network information flow a deterministic approach"
    - "wireless network simplification the gaussian n relay diamond network"
    - "a simple cooperative diversity method based on network path selection"

Connected through hyperedge HE-5 (induced by source paper "the capacity of the relay channel solution to cover s problem in the gaussian case"):
  with members:
    - "cover s open problem the capacity of the relay channel"
    - "improving on the cut set bound via geometric analysis of typical sets"

Connected through hyperedge HE-6 (induced by source paper "on the optimality of simple schedules for networks with multiple half duplex relays"):
  with members:
    - "on the gaussian half duplex relay channel"
    - "gaussian half duplex relay networks improved constant gap and connections with the assignment problem"
    - "achieving the capacity of the n relay gaussian diamond network within log n bits"
    - "capacity of gaussian channels with duty cycle and power constraints"
    - "on capacity and optimal scheduling for the half duplex multiple relay channel"
    - "efficient capacity computation and power optimization for relay networks"
    - "wireless network information flow a deterministic approach"
    - "learning with submodular functions a convex optimization perspective"

Connected through hyperedge HE-7 (induced by source paper "network simplification in half duplex building on submodularity"):
  with members:
    - "on the impact of a single edge on the network coding capacity"
    - "on network simplification for gaussian half duplex diamond networks"
    - "the approximate optimality of simple schedules for half duplex multi relay networks"
    - "gaussian half duplex relay networks improved constant gap and connections with the assignment problem"
    - "wireless network simplification the gaussian n relay diamond network"

Connected through hyperedge HE-8 (induced by source paper "improving on the cut set bound via geometric analysis of typical sets"):
  with members:
    - "wireless network information flow a deterministic approach"
    - "compute and forward harnessing interference through structured codes"
    - "communication requirements for generating correlated random variables"
    - "capacity of a class of modulo sum relay channels"

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)