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: "the approximate optimality of simple schedules for half duplex multi relay networks"
  Abstract: In ISIT2012 Brahma, Ozgur and Fragouli conjectured that in a half-duplex diamond relay network (a Gaussian noise network without a direct source-destination link and with N non-interfering relays) an approximately optimal relay scheduling (achieving the cut-set upper bound to within a constant gap uniformly over all channel gains) exists with at most N + 1 active states (only N + 1 out of the 2N possible relay listen-transmit configurations have a strictly positive probability). Such relay scheduling policies are said to be simple. In ITW2013 we conjectured that simple relay policies are optimal for any half-duplex Gaussian multi-relay network, that is, simple schedules are not a consequence of the diamond network's sparse topology. In this paper we formally prove the conjecture beyond Gaussian networks. In particular, for any memoryless half-duplex N-relay network for which the cut-set bound is approximately optimal to within a constant gap under some conditions (satisfied for example by Gaussian networks), an optimal schedule exists with at most N + 1 active states. The key step of our proof is to write the minimum of a submodular function by means of its Lovasz extension and use the greedy algorithm for submodular polyhedra to highlight structural properties of the optimal solution. This, together with the saddle-point property of min-max problems and the existence of optimal basic feasible solutions in linear programs, proves the claim.

Connected through hyperedge HE-1 (induced by source paper "efficiently finding simple schedules in gaussian half duplex relay line networks"):
  with members:
    - "gaussian half duplex relay networks improved constant gap and connections with the assignment problem"
    - "on capacity and optimal scheduling for the half duplex multiple relay channel"
    - "wireless network information flow a deterministic approach"

Connected through hyperedge HE-2 (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"
    - "cut set bound is loose for gaussian 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-3 (induced by source paper "on network simplification for gaussian half duplex diamond networks"):
  with members:
    - "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-4 (induced by source paper "when are dynamic relaying strategies necessary in half duplex wireless networks"):
  with members:
    - "generalized diversity multiplexing tradeoff of half duplex relay networks"
    - "wireless network information flow a deterministic approach"
    - "the diversity multiplexing tradeoff of the mimo half duplex relay channel"
    - "cooperative multiplexing in the multiple antenna half duplex relay channel"
    - "diversity multiplexing tradeoff of the half duplex relay channel"

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)