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: "error correction in fast matrix multiplication and inverse"
  Abstract: We present new algorithms to detect and correct errors in the product of two matrices, or the inverse of a matrix, over an arbitrary field. Our algorithms do not require any additional information or encoding other than the original inputs and the erroneous output. Their running time is softly linear in the number of nonzero entries in these matrices when the number of errors is sufficiently small, and they also incorporate fast matrix multiplication so that the cost scales well when the number of errors is large. These algorithms build on the recent result of Gasieniec et al (2017) on correcting matrix products, as well as existing work on verification algorithms, sparse low-rank linear algebra, and sparse polynomial interpolation.

Connected through hyperedge HE-1 (induced by source paper "lu factorization with errors"):
  with members:
    - "what can and can t we do with sparse polynomials"
    - "certificates for triangular equivalence and rank profiles"
    - "linear time interactive certificates for the minimal polynomial and the determinant of a sparse matrix"
    - "efficiently correcting matrix products"
    - "essentially optimal interactive certificates in linear algebra"
    - "powers of tensors and fast matrix multiplication"
    - "parallel computation of echelon forms"
    - "simultaneous computation of the row and column rank profiles"

Connected through hyperedge HE-2 (induced by source paper "on nondeterministic derandomization of freivalds algorithm consequences avenues and algorithmic progress"):
  with members:
    - "near optimal linear decision trees for k sum and related problems"
    - "strong eth breaks with merlin and arthur short non interactive proofs of batch evaluation"
    - "threesomes degenerates and love triangles"
    - "powers of tensors and fast matrix multiplication"
    - "popular conjectures imply strong lower bounds for dynamic problems"
    - "3sum 3xor triangles"
    - "faster all pairs shortest paths via circuit complexity"
    - "deterministic algorithms for skewed matrix products"

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.SC(Symbolic Computation)