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 "computing quartet distance is equivalent to counting 4 cycles"):
  Abstract: The quartet distance is a measure of similarity used to compare two unrooted phylogenetic trees on the same set of $n$ leaves, defined as the number of subsets of four leaves related by a different topology in both trees. After a series of previous results, Brodal et al. [SODA 2013] presented an algorithm that computes this number in $\mathcal{O}(nd\log n)$ time, where $d$ is the maximum degree of a node. Our main contribution is a two-way reduction establishing that the complexity of computing the quartet distance between two trees on $n$ leaves is the same, up to polylogarithmic factors, as the complexity of counting 4-cycles in an undirected simple graph with $m$ edges. The latter problem has been extensively studied, and the fastest known algorithm by Vassilevska Williams [SODA 2015] works in $\mathcal{O}(m^{1.48})$ time. In fact, even for the seemingly simpler problem of detecting a 4-cycle, the best known algorithm works in $\mathcal{O}(m^{4/3})$ time, and a conjecture of Yuster and Zwick implies that this might be optimal. In particular, an almost-linear time for computing the quartet distance would imply a surprisingly efficient algorithm for counting 4-cycles. In the other direction, by plugging in the state-of-the-art algorithms for counting 4-cycles, our reduction allows us to significantly decrease the complexity of computing the quartet distance. For trees with unbounded degrees we obtain an $\mathcal{O}(n^{1.48})$ time algorithm, which is a substantial improvement on the previous bound of $\mathcal{O}(n^{2}\log n)$. For trees with degrees bounded by $d$, by analysing the reduction more carefully, we are able to obtain an $\mathcal{\tilde O}(nd^{0.77})$ time algorithm, which is again a nontrivial improvement on the previous bound of $\mathcal{O}(nd\log n)$.

Includes members:
  Member "finding even cycles faster via capped k walks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "graph pattern detection hardness for all induced patterns and faster non induced cycles")
  Member "on the maximum quartet distance between phylogenetic trees":
    also connected through other hyperedges:
      (none)
  Member "powers of tensors and fast matrix multiplication":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "new algorithms and hardness for incremental single source shortest paths in directed graphs")
  Member "popular conjectures imply strong lower bounds for dynamic problems":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "new algorithms and hardness for incremental single source shortest paths in directed graphs")
  Member "comparing and aggregating partially resolved trees":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "on the weighted quartet consensus problem")
  Member "maintaining information in fully dynamic trees with top trees":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "coarse grained complexity for dynamic algorithms")

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)