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: "a nearly tight sum of squares lower bound for the planted clique problem"
  Abstract: We prove that with high probability over the choice of a random graph $G$ from the Erd\H{o}s-R\'enyi distribution $G(n,1/2)$, the $n^{O(d)}$-time degree $d$ Sum-of-Squares semidefinite programming relaxation for the clique problem will give a value of at least $n^{1/2-c(d/\log n)^{1/2}}$ for some constant $c>0$. This yields a nearly tight $n^{1/2 - o(1)}$ bound on the value of this program for any degree $d = o(\log n)$. Moreover we introduce a new framework that we call \emph{pseudo-calibration} to construct Sum of Squares lower bounds. This framework is inspired by taking a computational analog of Bayesian probability theory. It yields a general recipe for constructing good pseudo-distributions (i.e., dual certificates for the Sum-of-Squares semidefinite program), and sheds further light on the ways in which this hierarchy differs from others.

Connected through hyperedge HE-1 (induced by source paper "broadcast congested clique planted cliques and pseudorandom generators"):
  with members:
    - "congested clique algorithms for graph spanners"
    - "optimal lower bounds for distributed and streaming spanning forest computation"
    - "msf and connectivity in limited variants of the congested clique"
    - "a time hierarchy theorem for the local model"
    - "on derandomizing local distributed algorithms"
    - "deterministic subgraph detection in broadcast congest"
    - "towards a complexity theory for the congested clique"
    - "deterministic graph connectivity in the broadcast congested clique"

Connected through hyperedge HE-2 (induced by source paper "the kikuchi hierarchy and tensor pca"):
  with members:
    - "the power of sum of squares for detecting hidden structures"
    - "sum of squares certificates for maxima of random tensors on the sphere"
    - "multiplicative approximations for polynomial optimization over the unit sphere"
    - "mutual information for symmetric rank one matrix estimation a proof of the replica formula"
    - "strongly refuting random csps below the spectral threshold"
    - "phase transitions in sparse pca"
    - "how to refute a random csp"
    - "asymptotic mutual information for the two groups stochastic block model"

Connected through hyperedge HE-3 (induced by source paper "computational hardness of certifying bounds on constrained pca problems"):
  with members:
    - "mean field approximation convex hierarchies and the optimality of correlation rounding a unified perspective"
    - "heterogeneous multireference alignment a single pass approach"
    - "community detection in hypergraphs spiked tensor models and sum of squares"
    - "the lov asz theta function for random regular graphs and community detection in the hard regime"
    - "the power of sum of squares for detecting hidden structures"
    - "bayesian estimation from few samples community detection and related problems"
    - "sum of squares lower bounds for refuting any csp"
    - "mutual information in rank one matrix estimation"

Connected through hyperedge HE-4 (induced by source paper "extended formulation lower bounds for refuting random csps"):
  with members:
    - "sum of squares lower bounds for refuting any csp"
    - "approximating rectangles by juntas and weakly exponential lower bounds for lp relaxations of csps"
    - "strongly refuting random csps below the spectral threshold"
    - "how to refute a random csp"
    - "complexity theoretic limitations on learning halfspaces"
    - "tensor prediction rademacher complexity and random 3 xor"
    - "lower bounds on the size of semidefinite programming relaxations"
    - "analysis of boolean functions"

Connected through hyperedge HE-5 (induced by source paper "lifting sum of squares lower bounds degree 2 to degree 4"):
  with members:
    - "extended formulation lower bounds for refuting random csps"
    - "the threshold for sdp refutation of random regular nae 3sat"
    - "the power of sum of squares for detecting hidden structures"
    - "sum of squares lower bounds for refuting any csp"
    - "strongly refuting random csps below the spectral threshold"
    - "improved sum of squares lower bounds for hidden clique and hidden submatrix problems"
    - "semidefinite programs on sparse random graphs and their application to community detection"

Connected through hyperedge HE-6 (induced by source paper "the average case complexity of counting cliques in erdos renyi hypergraphs"):
  with members:
    - "optimal average case reductions to sparse pca from weak assumptions to strong hardness"
    - "reducibility and computational lower bounds for problems with planted sparse structure"
    - "on independent sets in random graphs"
    - "incoherence optimal matrix completion"
    - "hidden cliques and the certification of the restricted isometry property"
    - "nuclear norm minimization for the planted clique and biclique problems"

Connected through hyperedge HE-7 (induced by source paper "on the power of symmetric linear programs"):
  with members:
    - "definable inapproximability new challenges for duplicator"
    - "on symmetric circuits and fixed point logics"
    - "approximate constraint satisfaction requires large lp relaxations"
    - "the matching polytope has exponential extension complexity"

Connected through hyperedge HE-8 (induced by source paper "exact recovery for a family of community detection generative models"):
  with members:
    - "does robustness imply tractability a lower bound for planted clique in the semi random model"
    - "community detection in hypergraphs spiked tensor models and sum of squares"
    - "information theoretic bounds for exact recovery in weighted stochastic block models using the renyi divergence"
    - "exact recovery in the stochastic block model"

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.CC(Computational Complexity)