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: "estimation and registration on graphs"
  Abstract: A statistical framework is introduced for a broad class of problems involving synchronization or registration of data across a sensor network in the presence of noise. This framework enables an estimation-theoretic approach to the design and characterization of synchronization algorithms. The Fisher information is expressed in terms of the distribution of the measurement noise and standard mathematical descriptors of the network's graph structure for several important cases. This leads to maximum likelihood and approximate maximum-likelihood registration algorithms and also to distributed iterative algorithms that, when they converge, attain statistically optimal solutions. The relationship between optimal estimation in this setting and Kirchhoff's laws is also elucidated.

Connected through hyperedge HE-1 (induced by source paper "the noise sensitivity phase transition in spectral group synchronization over compact groups"):
  with members:
    - "message passing algorithms for synchronization problems over compact groups"
    - "spectral synchronization of multiple views in se 3"
    - "non unique games over compact groups and orientation estimation in cryo em"
    - "synchronization over z2 and community detection in signed multiplex networks with constraints"
    - "a solution for multi alignment by transformation synchronisation"
    - "cramer rao bounds for synchronization of rotations"
    - "multireference alignment using semidefinite programming"
    - "exact and stable recovery of rotations for robust synchronization"

Connected through hyperedge HE-2 (induced by source paper "concentration of the kirchhoff index for erdős renyi graphs"):
  with members:
    - "cramer rao bounds for synchronization of rotations"
    - "exact and stable recovery of rotations for robust synchronization"
    - "eigenvector synchronization graph rigidity and the molecule problem"

Connected through hyperedge HE-3 (induced by source paper "cramer rao bounds for synchronization of rotations"):
  with members:
    - "exact and stable recovery of rotations for robust synchronization"
    - "eigenvector synchronization graph rigidity and the molecule problem"

Connected through hyperedge HE-4 (induced by source paper "global registration of multiple point clouds using semidefinite programming"):
  with members:
    - "robust computation of linear models by convex relaxation"
    - "manopt a matlab toolbox for optimization on manifolds"
    - "approximating the little grothendieck problem over the orthogonal and unitary groups"
    - "incremental computation of pseudo inverse of laplacian theory and applications"
    - "exact and stable recovery of rotations for robust synchronization"
    - "efficient rounding for the noncommutative grothendieck inequality"
    - "eigenvector synchronization graph rigidity and the molecule problem"
    - "phaselift exact and stable signal recovery from magnitude measurements via convex programming"

Connected through hyperedge HE-5 (induced by source paper "exact and stable recovery of rotations for robust synchronization"):
  with members:
    - "cramer rao bounds for synchronization of rotations"
    - "efficient rounding for the noncommutative grothendieck inequality"
    - "eigenvector synchronization graph rigidity and the molecule problem"
    - "max cut and the smallest eigenvalue"

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.NI(Networking and Internet Architecture)