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 "on the complexity of computing prime tables"):
  Abstract: Many large arithmetic computations rely on tables of all primes less than $n$. For example, the fastest algorithms for computing $n!$ takes time $O(M(n\log n) + P(n))$, where $M(n)$ is the time to multiply two $n$-bit numbers, and $P(n)$ is the time to compute a prime table up to $n$. The fastest algorithm to compute $\binom{n}{n/2}$ also uses a prime table. We show that it takes time $O(M(n) + P(n))$. #R##N#In various models, the best bound on $P(n)$ is greater than $M(n\log n)$, given advances in the complexity of multiplication \cite{Furer07,De08}. In this paper, we give two algorithms to computing prime tables and analyze their complexity on a multitape Turing machine, one of the standard models for analyzing such algorithms. These two algorithms run in time $O(M(n\log n))$ and $O(n\log^2 n/\log \log n)$, respectively. We achieve our results by speeding up Atkin's sieve. #R##N#Given that the current best bound on $M(n)$ is $n\log n 2^{O(\log^*n)}$, the second algorithm is faster and improves on the previous best algorithm by a factor of $\log^2\log n$. Our fast prime-table algorithms speed up both the computation of $n!$ and $\binom{n}{n/2}$. #R##N#Finally, we show that computing the factorial takes $\Omega(M(n \log^{4/7 - \epsilon} n))$ for any constant $\epsilon > 0$ assuming only multiplication is allowed.

Includes members:
  Member "how fast can we multiply large integers on an actual computer":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "minimizing and computing the inverse geodesic length on trees")
  Member "fast integer multiplication using modular arithmetic":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "faster integer multiplication using short lattice vectors")

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.CC(Computational Complexity)