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 "improved algorithms for mst and metric tsp interdiction"):
  Abstract: We consider the {\em MST-interdiction} problem: given a multigraph $G = (V, E)$, edge weights $\{w_e\geq 0\}_{e \in E}$, interdiction costs $\{c_e\geq 0\}_{e \in E}$, and an interdiction budget $B\geq 0$, the goal is to remove a set $R\subseteq E$ of edges of total interdiction cost at most $B$ so as to maximize the $w$-weight of an MST of $G-R:=(V,E\setminus R)$. #R##N#Our main result is a $4$-approximation algorithm for this problem. This improves upon the previous-best $14$-approximation~\cite{Zenklusen15}. Notably, our analysis is also significantly simpler and cleaner than the one in~\cite{Zenklusen15}. Whereas~\cite{Zenklusen15} uses a greedy algorithm with an involved analysis to extract a good interdiction set from an over-budget set, we utilize a generalization of knapsack called the {\em tree knapsack problem} that nicely captures the key combinatorial aspects of this "extraction problem." We prove a simple, yet strong, LP-relative approximation bound for tree knapsack, which leads to our improved guarantees for MST interdiction. Our algorithm and analysis are nearly tight, as we show that one cannot achieve an approximation ratio better than 3 relative to the upper bound used in our analysis (and the one in~\cite{Zenklusen15}). #R##N#Our guarantee for MST-interdiction yields an $8$-approximation for {\em metric-TSP interdiction} (improving over the $28$-approximation in~\cite{Zenklusen15}). We also show that the {\em maximum-spanning-tree interdiction} problem is at least as hard to approximate as the minimization version of densest-$k$-subgraph.

Includes members:
  Member "an o 1 approximation for minimum spanning tree interdiction":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "downgrading to minimize connectivity")
  Member "improved region growing and combinatorial algorithms for k route cut problems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "downgrading to minimize connectivity")
  Member "reducing the rank of a matroid":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a parameterized algorithm for mixed cut")

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)