human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "fast computation of smith forms of sparse matrices over local rings"):
  Abstract: We present algorithms to compute the Smith Normal Form of matrices over two families of local rings. #R##N#The algorithms use the \emph{black-box} model which is suitable for sparse and structured matrices. The algorithms depend on a number of tools, such as matrix rank computation over finite fields, for which the best-known time- and memory-efficient algorithms are probabilistic. #R##N#For an $\nxn$ matrix $A$ over the ring $\Fzfe$, where $f^e$ is a power of an irreducible polynomial $f \in \Fz$ of degree $d$, our algorithm requires $\bigO(\eta de^2n)$ operations in $\F$, where our black-box is assumed to require $\bigO(\eta)$ operations in $\F$ to compute a matrix-vector product by a vector over $\Fzfe$ (and $\eta$ is assumed greater than $\Pden$). The algorithm only requires additional storage for $\bigO(\Pden)$ elements of $\F$. In particular, if $\eta=\softO(\Pden)$, then our algorithm requires only $\softO(n^2d^2e^3)$ operations in $\F$, which is an improvement on known dense methods for small $d$ and $e$. #R##N#For the ring $\ZZ/p^e\ZZ$, where $p$ is a prime, we give an algorithm which is time- and memory-efficient when the number of nontrivial invariant factors is small. We describe a method for dimension reduction while preserving the invariant factors. The time complexity is essentially linear in $\mu n r e \log p,$ where $\mu$ is the number of operations in $\ZZ/p\ZZ$ to evaluate the black-box (assumed greater than $n$) and $r$ is the total number of non-zero invariant factors. #R##N#To avoid the practical cost of conditioning, we give a Monte Carlo certificate, which at low cost, provides either a high probability of success or a proof of failure. The quest for a time- and memory-efficient solution without restrictions on the number of nontrivial invariant factors remains open. We offer a conjecture which may contribute toward that end.

Includes members:
  Member "on finding multiplicities of characteristic polynomial factors of black box matrices":
    also connected through other hyperedges:
      (none)
  Member "a local construction of the smith normal form of a matrix polynomial":
    also connected through other hyperedges:
      (none)
  Member "faster inversion and other black box matrix computations using efficient block projections":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "minimal representations and algebraic relations for single nested products")

Question: Please tell me which class the source paper 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)