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: "lower bounds for matrix product"
  Abstract: We prove lower bounds on the number of product gates in bilinear and quadratic circuits that compute the product of two $n \cross n$ matrices over finite fields. In particular we obtain the following results: #R##N#1. We show that the number of product gates in any bilinear (or quadratic) circuit that computes the product of two $n \cross n$ matrices over $F_2$ is at least $3 n^2 - o(n^2)$. #R##N#2. We show that the number of product gates in any bilinear circuit that computes the product of two $n \cross n$ matrices over $F_p$ is at least $(2.5 + \frac{1.5}{p^3 -1})n^2 -o(n^2)$. #R##N#These results improve the former results of Bshouty '89 and Blaser '99 who proved lower bounds of $2.5 n^2 - o(n^2)$.

Connected through hyperedge HE-1 (induced by source paper "fast feasible and unfeasible matrix multiplication"):
  with members:
    - "hypergraph partitioning for sparse matrix matrix multiplication"
    - "exploiting multiple levels of parallelism in sparse matrix matrix multiplication"
    - "an improved combinatorial algorithm for boolean matrix multiplication"
    - "improving the numerical stability of fast matrix multiplication algorithms"
    - "a framework for practical parallel fast matrix multiplication"
    - "fast matrix multiplication limitations of the laser method"
    - "powers of tensors and fast matrix multiplication"
    - "nearly optimal computations with structured matrices"

Connected through hyperedge HE-2 (induced by source paper "on multilinear forms bias correlation and tensor rank"):
  with members:
    - "barriers for rank methods in arithmetic complexity"
    - "the chasm at depth four and tensor rank old results new insights"
    - "tensor rank some lower and upper bounds"

Connected through hyperedge HE-3 (induced by source paper "spectrum approximation beyond fast matrix multiplication algorithms and hardness"):
  with members:
    - "fast estimation of approximate matrix ranks using spectral densities"
    - "improved rectangular matrix multiplication using powers of the coppersmith winograd tensor"
    - "embeddings of schatten norms with applications to data streams"
    - "improved stochastic trace estimation using mutually unbiased bases"
    - "weighted schatten p norm minimization for image denoising and background subtraction"
    - "sketches for matrix norms faster smaller and more general"
    - "solving ridge regression using sketched preconditioned svrg"
    - "faster eigenvector computation via shift and invert preconditioning"

Connected through hyperedge HE-4 (induced by source paper "tensor rank some lower and upper bounds"):
  with members:
    - "an improvement on ranks of explicit tensors"

Connected through hyperedge HE-5 (induced by source paper "near quadratic matrix multiplication modulo composites"):
  with members:
    - "computing elementary symmetric polynomials with a sublinear number of multiplications"

Connected through hyperedge HE-6 (induced by source paper "defying dimensions mod 6"):
  with members:
    - "near quadratic matrix multiplication modulo composites"

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)