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: "matrix rigidity and the croot lev pach lemma"
  Abstract: Matrix rigidity is a notion put forth by Valiant as a means for proving arithmetic circuit lower bounds. A matrix is rigid if it is far, in Hamming distance, from any low rank matrix. Despite decades of efforts, no explicit matrix rigid enough to carry out Valiant's plan has been found. Recently, Alman and Williams showed, contrary to common belief, that the $2^n \times 2^n$ Hadamard matrix could not be used for Valiant's program as it is not sufficiently rigid. In this note we observe a similar `non rigidity' phenomena for any $q^n \times q^n$ matrix $M$ of the form $M(x,y) = f(x+y)$, where $f:F_q^n \to F_q$ is any function and $F_q$ is a fixed finite field of $q$ elements ($n$ goes to infinity). The theorem follows almost immediately from a recent lemma of Croot, Lev and Pach which is also the main ingredient in the recent solution of the cap-set problem.

Connected through hyperedge HE-1 (induced by source paper "the generalized orthogonality dimension of generalized kneser graphs bounds and applications"):
  with members:
    - "improved hardness for h colourings of g colourable graphs"
    - "approximating the orthogonality dimension of graphs and hypergraphs"
    - "on a fractional version of haemers bound"
    - "algebraic approach to promise constraint satisfaction"
    - "on minrank and forbidden subgraphs"
    - "probabilistic rank and matrix rigidity"
    - "linear index coding via semidefinite programming"
    - "conditional hardness for approximate coloring"

Connected through hyperedge HE-2 (induced by source paper "equivalence of systematic linear data structures and matrix rigidity"):
  with members:
    - "static data structure lower bounds imply rigidity"
    - "crossing the logarithmic barrier for dynamic boolean data structure lower bounds"
    - "probabilistic rank and matrix rigidity"
    - "unifying and strengthening hardness for dynamic problems via the online matrix vector multiplication conjecture"
    - "new unconditional hardness results for dynamic and online problems"
    - "adapt or die polynomial lower bounds for non adaptive dynamic data structures"
    - "min rank conjecture for log depth circuits"
    - "the cell probe complexity of dynamic range counting"

Connected through hyperedge HE-3 (induced by source paper "lower bounds for matrix factorization"):
  with members:
    - "non malleable extractors and non malleable codes partially optimal constructions"
    - "static data structure lower bounds imply rigidity"
    - "crossing the logarithmic barrier for dynamic boolean data structure lower bounds"
    - "probabilistic rank and matrix rigidity"
    - "hitting sets for roabp and sum of set multilinear circuits"
    - "improved bounds for reduction to depth 4 and depth 3"
    - "on identity testing of tensors low rank recovery and compressed sensing"
    - "the cell probe complexity of dynamic range counting"

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)