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 "an improved algorithm for dynamic set cover"):
  Abstract: We consider the minimum set cover problem in a dynamic setting. Here, we are given a universe of elements $\mathcal{U}$ and a collection of sets $\mathcal{S} \subseteq 2^{\mathcal{U}}$ as input, where each set $s \in \mathcal{S}$ has a cost $1/C   1$. The input keeps changing via a sequence of updates. Each update inserts/deletes an element in the universe, and specifies the sets in $§$ containing that element. The goal is to maintain a set cover of (approximately) minimum cost with as small update time as possible. Let $n$ denote the number of sets in $\mathcal{S}$, and let $m$ and $f$ respectively denote the maximum number of elements in the universe and the maximum frequency of an element across all the updates. #R##N#This problem has received significant attention in recent years in the dynamic algorithms community. Gupta et al. [STOC `17] designed a deterministic $\Theta(\log m)$-approximation algorithm for this problem that has an update time of $O(f \log m)$. On the other hand, the line of work by Bhattacharya et al. [ICALP `15], Bhattacharya et al. [IPCO `17], Gupta et al. [STOC `17], Abboud et al. [STOC `19] and Bhattacharya et al. [FOCS `19] very recently led to a deterministic $(1+\epsilon)f$-approximation algorithm with $O(f \log (Cm)/\epsilon^2)$ update time. #R##N#In this paper, we obtain the first dynamic algorithm for this problem with near-optimal approximation ratio whose update time is independent of $m, n$. Specifically, our algorithm is deterministic and it achieves an approximation ratio of $(1+\epsilon)f$ and an update time of $O\left((f^2/\epsilon^3)+(f/\epsilon^2) \log C\right)$. Our algorithm is based on the dynamic primal-dual framework, and it carefully combines the ideas from the dynamic vertex cover algorithm of Bhattacharya and Kulkarni [SODA `19] and the dynamic set cover algorithm of Bhattacharya et al. [FOCS `19].

Includes members:
  Member "a new deterministic algorithm for dynamic set cover":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "practice of streaming and dynamic graphs concepts models systems and parallelism")
  Member "deterministic fully dynamic approximate vertex cover and fractional matching in o 1 amortized update time":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "dynamic geometric set cover and hitting set")
  Member "fully dynamic maximal matching in constant update time":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "dynamic graph algorithms with batch updates in the massively parallel computation model")
  Member "online and dynamic algorithms for set cover":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "the power of recourse better algorithms for facility location in online and dynamic models")
  Member "design of dynamic algorithms via primal dual method":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "dynamic geometric set cover and hitting set")
  Member "deterministic fully dynamic data structures for vertex cover and matching":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "coarse grained complexity for dynamic algorithms")
  Member "analytical approach to parallel repetition":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "dynamic geometric set cover and hitting set")
  Member "simple deterministic algorithms for fully dynamic maximal matching":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "dynamic graph algorithms with batch updates in the massively parallel computation model")

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.DS(Data Structures and Algorithms)