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: "probabilistic rank and matrix rigidity"
  Abstract: We consider a notion of probabilistic rank and probabilistic sign-rank of a matrix, which measures the extent to which a matrix can be probabilistically represented by low-rank matrices. We demonstrate several connections with matrix rigidity, communication complexity, and circuit lower bounds, including: #R##N#The Walsh-Hadamard Transform is Not Very Rigid. We give surprising upper bounds on the rigidity of a family of matrices whose rigidity has been extensively studied, and was conjectured to be highly rigid. For the $2^n \times 2^n$ Walsh-Hadamard transform $H_n$ (a.k.a. Sylvester matrices, or the communication matrix of Inner Product mod 2), we show how to modify only $2^{\epsilon n}$ entries in each row and make the rank drop below $2^{n(1-\Omega(\epsilon^2/\log(1/\epsilon)))}$, for all $\epsilon > 0$, over any field. That is, it is not possible to prove arithmetic circuit lower bounds on Hadamard matrices, via L. Valiant's matrix rigidity approach. We also show non-trivial rigidity upper bounds for $H_n$ with smaller target rank. #R##N#Matrix Rigidity and Threshold Circuit Lower Bounds. We give new consequences of rigid matrices for Boolean circuit complexity. We show that explicit $n \times n$ Boolean matrices which maintain rank at least $2^{(\log n)^{1-\delta}}$ after $n^2/2^{(\log n)^{\delta/2}}$ modified entries would yield a function lacking sub-quadratic-size $AC^0$ circuits with two layers of arbitrary linear threshold gates. We also prove that explicit 0/1 matrices over $\mathbb{R}$ which are modestly more rigid than the best known rigidity lower bounds for sign-rank would imply strong lower bounds for the infamously difficult class $THR\circ THR$.

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"
    - "matrix rigidity and the croot lev pach lemma"
    - "linear index coding via semidefinite programming"
    - "conditional hardness for approximate coloring"

Connected through hyperedge HE-2 (induced by source paper "approximate is good enough probabilistic variants of dimensional and margin complexity"):
  with members:
    - "backward feature correction how deep learning performs deep learning"
    - "on the power and limitations of random features for understanding neural networks"
    - "neural tangent kernel convergence and generalization in neural networks"
    - "sgd learns the conjugate kernel class of the network"
    - "super linear gate and super quadratic wire lower bounds for depth two and depth three threshold circuits"

Connected through hyperedge HE-3 (induced by source paper "equivalence of systematic linear data structures and matrix rigidity"):
  with members:
    - "static data structure lower bounds imply rigidity"
    - "matrix rigidity and the croot lev pach lemma"
    - "crossing the logarithmic barrier for dynamic boolean data structure lower bounds"
    - "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-4 (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"
    - "matrix rigidity and the croot lev pach lemma"
    - "crossing the logarithmic barrier for dynamic boolean data structure lower bounds"
    - "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"

Connected through hyperedge HE-5 (induced by source paper "toward super polynomial size lower bounds for depth two threshold circuits"):
  with members:
    - "on the hardness of approximate and exact bichromatic maximum inner product"
    - "tighter connections between formula sat and shaving logs"
    - "limits on representing boolean functions by linear combinations of simple functions thresholds relus and low degree polynomials"
    - "fine grained complexity meets ip pspace"
    - "weights at the bottom matter when the top is heavy"
    - "simulating branching programs with edit distance and friends or a polylog shaved is a lower bound made"
    - "super linear gate and super quadratic wire lower bounds for depth two and depth three threshold circuits"
    - "new algorithms and lower bounds for circuits with linear threshold gates"

Connected through hyperedge HE-6 (induced by source paper "a tight lower bound for counting hamiltonian cycles via matrix rank"):
  with members:
    - "parameterizing the permanent genus apices minors evaluation mod 2 k"
    - "the parity of directed hamiltonian cycles"
    - "fast hamiltonicity checking via bases of perfect matchings"
    - "determinant sums for undirected hamiltonicity"

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)