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: "worst case robust multiuser transmit beamforming using semidefinite relaxation duality and implications"
  Abstract: This paper studies a downlink multiuser transmit beamforming design under spherical channel uncertainties, using a worst-case robust formulation. This robust design problem is nonconvex. Recently, a convex approximation formulation based on semidefinite relaxation (SDR) has been proposed to handle the problem. Curiously, simulation results have consistently indicated that SDR can attain the global optimum of the robust design problem. This paper intends to provide some theoretical insights into this important empirical finding. Our main result is a dual representation of the SDR formulation, which reveals an interesting linkage to a different robust design problem, and the possibility of SDR optimality.

Connected through hyperedge HE-1 (induced by source paper "unraveling the rank one solution mystery of robust miso downlink transmit optimization a verifiable sufficient condition via a new duality result"):
  with members:
    - "coordinate update algorithms for robust power loading for the mu miso downlink with outage constraints"
    - "a parallel decomposition method for nonconvex stochastic multi agent optimization problems"
    - "a stochastic beamformed amplify and forward scheme in a multigroup multicast mimo relay network with per antenna power constraints"
    - "optimal multiuser transmit beamforming a difficult problem with a simple solution structure"
    - "physical layer multicasting by stochastic transmit beamforming and alamouti space time coding"
    - "distributed robust multicell coordinated beamforming with imperfect csi an admm approach"
    - "robust linear precoder design for multi cell downlink transmission"
    - "outage constrained robust transmit optimization for multiuser miso downlinks tractable approximations by conic optimization"

Connected through hyperedge HE-2 (induced by source paper "distributed robust multicell coordinated beamforming with imperfect csi an admm approach"):
  with members:
    - "robust monotonic optimization framework for multicell miso systems"
    - "worst case sinr constrained robust coordinated beamforming for multicell wireless systems"
    - "robust linear precoder design for multi cell downlink transmission"
    - "multiuser miso transmitter optimization for intercell interference mitigation"
    - "probabilistic sinr constrained robust transmit beamforming a bernstein type inequality based conservative approach"
    - "optimal distributed beamforming for miso interference channels"
    - "cooperative interference management with miso beamforming"

Connected through hyperedge HE-3 (induced by source paper "outage constrained robust transmit optimization for multiuser miso downlinks tractable approximations by conic optimization"):
  with members:
    - "physical layer multicasting by stochastic transmit beamforming and alamouti space time coding"
    - "large system analysis of linear precoding in correlated miso broadcast channels under limited feedback"
    - "probabilistic sinr constrained robust transmit beamforming a bernstein type inequality based conservative approach"
    - "dynamic resource allocation in cognitive radio networks"
    - "training and feedback optimization for multiuser mimo downlink"
    - "multiuser mimo achievable rates with downlink training and channel state feedback"
    - "mimo broadcast channels with finite rate feedback"

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)