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: "on the i o complexity of hybrid algorithms for integer multiplication"
  Abstract: Almost asymptotically tight lower bounds are derived for the I/O complexity $IO\left(n,M\right)$ of a general class of hybrid algorithms computing the product of two integers, each represented with $n$ digits in a given base $s$, in a two-level storage hierarchy with $M$ words of fast memory, with different digits stored in different memory words. The considered hybrid algorithm combine the Toom-Cook-$k$ (or Toom-$k$) fast integer multiplication approach with computational complexity $\Theta\left(c_kn^{\log_k \left(2k-1\right)}\right)$, and "standard" integer multiplication algorithms which compute $\Omega\left(n^2\right)$ digit multiplications. #R##N#We present an $\Omega\left(\left(n/\max\{M,n_0\}\right)^{\log_k \left(2k-1\right)}\left(\max\{1,n_0/M\}\right)^2M\right)$ lower bound for the I/O complexity a class of "uniform, non-stationary" hybrid algorithms when executed in a two-level storage hierarchy with $M$ words of fast memory, where $n_0$ denotes the threshold size of sub-problems which are computed using standard algorithms with algebraic complexity $\Omega\left(n^2\right)$. #R##N#The lower bound is derived for the more general class of "non-uniform, non-stationary" hybrid algorithms which allow recursive calls to have a different structure, even when they refer to the multiplication of integers of the same size and in the same recursive level including those where the value of $k$ is allowed to vary with the level of recursion. As some hybrid algorithms from this class execute a number of I/O operations that is within a $O\left(k^2\right)$ multiplicative term of the corresponding lower bounds, the proposed lower bounds are almost asymptotically tight and indeed tight for constant values of $k$. #R##N#Extensions of the lower bounds for a parallel model with $P$ processors are also discussed.

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)