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: "rank constrained schur convex optimization with multiple trace log det constraints"
  Abstract: Rank-constrained optimization problems have received an increasing intensity of interest recently, because many optimization problems in communications and signal processing applications can be cast into a rank-constrained optimization problem. However, due to the nonconvex nature of rank constraints, a systematic solution to general rank-constrained problems has remained open for a long time. In this paper, we focus on a rank-constrained optimization problem with a Schur-convex/concave objective function and multiple trace/log-determinant constraints. We first derive a structural result on the optimal solution of the rank-constrained problem using majorization theory. Based on the solution structure, we transform the rank-constrained problem into an equivalent problem with a unitary constraint. After that, we derive an iterative projected steepest descent algorithm which converges to a local optimal solution. Furthermore, we shall show that under some special cases, we can derive a closed-form global optimal solution. The numerical results show the superior performance of our proposed technique over the baseline schemes.

Connected through hyperedge HE-1 (induced by source paper "cognitive beamforming for multiple secondary data streams with individual snr constraints"):
  with members:
    - "multiuser mimo downlink beamforming design based on group maximum sinr filtering"
    - "optimal spectrum sharing in mimo cognitive radio networks via semidefinite programming"
    - "exploiting multi antennas for opportunistic spectrum sharing in cognitive radio networks"

Connected through hyperedge HE-2 (induced by source paper "linear precoding and equalization for network mimo with partial cooperation"):
  with members:
    - "multi cell mimo downlink with cell cooperation and fair scheduling a large system limit analysis"
    - "mimo b mac interference network optimization under rate constraints by polite water filling and duality"
    - "optimal multiuser zero forcing with per antenna power constraints for network mimo coordination"
    - "adaptive beamforming in interference networks via bi directional training"
    - "duality polite water filling and optimization for mimo b mac interference networks and itree networks"
    - "multiuser miso transmitter optimization for intercell interference mitigation"
    - "linear precoding in cooperative mimo cellular networks with limited coordination clusters"
    - "cooperative algorithms for mimo interference channels"

Connected through hyperedge HE-3 (induced by source paper "mimo precoding in underlay cognitive radio systems with completely unknown primary csi"):
  with members:
    - "interference alignment as a rank constrained rank minimization"
    - "beamforming and rate allocation in miso cognitive radio networks"
    - "optimal spectrum sharing in mimo cognitive radio networks via semidefinite programming"
    - "exploiting multi antennas for opportunistic spectrum sharing in cognitive radio networks"
    - "on the capacity of doubly correlated mimo 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)