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 "minimizing and computing the inverse geodesic length on trees"):
  Abstract: The inverse geodesic length (IGL) of a graph $G=(V,E)$ is the sum of inverse distances between every two vertices: $IGL(G) = \sum_{\{u,v\} \subseteq V} \frac{1}{d_G(u,v)}$. In the MinIGL problem, the input is a graph $G$, an integer $k$, and a target inverse geodesic length $T$, and the question is whether there are $k$ vertices whose deletion decreases the IGL of $G$ to at most $T$. Aziz et al. (2018) proved that MinIGL is $W[1]$-hard for parameter treewidth, but the complexity status of the problem remains open in the case where $G$ is a tree. We show that MinIGL on trees is subexponential by giving a $2^{O\left((n \log n)^{5/6}\right)}$ time, polynomial space algorithm, where $n$ is the number of vertices of the input graph. #R##N#The distance distribution of a graph $G$ is a sequence $\{a_i\}$ describing the number of vertex pairs distance $i$ apart in $G$: $a_i = |\{ \{u, v\}: d_G(u, v) = i\}|$. Given only the distance distribution, one can easily determine graph parameters such as diameter, Wiener index, and particularly, the IGL. We show that the distance distribution of a tree can be computed in $O(n \log^2 n)$ time by reduction to polynomial multiplication. We also extend the result to graphs of bounded treewidth by showing that the first $P$ values of the distance distribution can be computed in $2^{O(\text{tw}(G))} n^{1 + \varepsilon} \sqrt{P}$ time.

Includes members:
  Member "multivariate analysis of orthogonal range searching and graph distances parameterized by treewidth":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "diameter computation on h minor free graphs and graphs of bounded distance vc dimension")
  Member "how fast can we multiply large integers on an actual computer":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a near linear pseudopolynomial time algorithm for subset sum")

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)