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 "superlinear lower bounds for distributed subgraph detection"):
  Abstract: In the distributed subgraph-freeness problem, we are given a graph $H$, and asked to determine whether the network graph contains $H$ as a subgraph or not. Subgraph-freeness is an extremely local problem: if the network had no bandwidth constraints, we could detect any subgraph $H$ in $|H|$ rounds, by having each node of the network learn its entire $|H|$-neighborhood. However, when bandwidth is limited, the problem becomes harder. #R##N#Upper and lower bounds in the presence of congestion have been established for several classes of subgraphs, including cycles, trees, and more complicated subgraphs. All bounds shown so far have been linear or sublinear. We show that the subgraph-freeness problem is not, in general, solvable in linear time: for any $k \geq 2$, there exists a subgraph $H_k$ such that $H_k$-freeness requires $\Omega( n^{2-1/k} / (Bk) )$ rounds to solve. Here $B$ is the bandwidth of each communication link. The lower bound holds even for diameter-3 subgraphs and diameter-3 network graphs. In particular, taking $k = \Theta(\log n)$, we obtain a lower bound of $\Omega(n^2 / (B \log n))$.

Includes members:
  Member "fooling views a new lower bound technique for distributed computations under congestion":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "distributed testing of graph isomorphism in the congest model")
  Member "faster and simpler distributed algorithms for testing and correcting graph properties in the congest model":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "distributed testing of graph isomorphism in the congest model")
  Member "quadratic and near quadratic lower bounds for the congest model":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "distributed maximum matching verification in congest")
  Member "deterministic subgraph detection in broadcast congest":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "distributed testing of graph isomorphism in the congest model")
  Member "near linear lower bounds for distributed distance computations even in sparse networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "beyond alice and bob improved inapproximability for maximum independent set in congest")
  Member "algebraic methods in the congested clique":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "exponentially faster shortest paths in the congested clique")
  Member "tri tri again finding triangles and small subgraphs in a distributed setting":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "parallel algorithms for small subgraph counting")

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)