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: "sample complexity of the boolean multireference alignment problem"
  Abstract: The Boolean multireference alignment problem consists in recovering a Boolean signal from multiple shifted and noisy observations. In this paper we obtain an expression for the error exponent of the maximum A posteriori decoder. This expression is used to characterize the number of measurements needed for signal recovery in the low SNR regime, in terms of higher order autocorrelations of the signal. The characterization is explicit for various signal dimensions, such as prime and even dimensions.

Connected through hyperedge HE-1 (induced by source paper "spectral methods from tensor networks"):
  with members:
    - "message passing algorithms for synchronization problems over compact groups"
    - "estimation in the group action channel"
    - "bispectrum inversion with application to multireference alignment"
    - "heterogeneous multireference alignment a single pass approach"
    - "the sample complexity of multi reference alignment"
    - "exact tensor completion with sum of squares"
    - "a nearly tight sum of squares lower bound for the planted clique problem"
    - "polynomial time tensor decompositions with sum of squares"

Connected through hyperedge HE-2 (induced by source paper "estimation in the group action channel"):
  with members:
    - "bispectrum inversion with application to multireference alignment"
    - "multireference alignment is easier with an aperiodic translation distribution"
    - "a certifiably correct algorithm for synchronization over the special euclidean group"
    - "f divergence inequalities"

Connected through hyperedge HE-3 (induced by source paper "the sample complexity of multi reference alignment"):
  with members:
    - "bispectrum inversion with application to multireference alignment"
    - "multireference alignment is easier with an aperiodic translation distribution"
    - "a representation theory perspective on simultaneous alignment and classification"
    - "fundamental limits in multi image alignment"
    - "non unique games over compact groups and orientation estimation in cryo em"
    - "multireference alignment using semidefinite programming"
    - "fourier pca and robust tensor decomposition"
    - "settling the polynomial learnability of mixtures of gaussians"

Connected through hyperedge HE-4 (induced by source paper "universal joint image clustering and registration using partition information"):
  with members:
    - "bispectrum inversion with application to multireference alignment"
    - "info clustering a mathematical theory for data clustering"
    - "universal clustering via crowdsourcing"
    - "fundamental limits in multi image alignment"

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)