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 "reducing path tsp to tsp"):
  Abstract: We present a black-box reduction from the path version of the Traveling Salesman Problem (Path TSP) to the classical tour version (TSP). More precisely, we show that given an $\alpha$-approximation algorithm for TSP, then, for any $\epsilon >0$, there is an $(\alpha+\epsilon)$-approximation algorithm for the more general Path TSP. This reduction implies that the approximability of Path TSP is the same as for TSP, up to an arbitrarily small error. This avoids future discrepancies between the best known approximation factors achievable for these two problems, as they have existed until very recently. #R##N#A well-studied special case of TSP, Graph TSP, asks for tours in unit-weight graphs. Our reduction shows that any $\alpha$-approximation algorithm for Graph TSP implies an $(\alpha+\epsilon)$-approximation algorithm for its path version. By applying our reduction to the $1.4$-approximation algorithm for Graph TSP by Sebő and Vygen, we obtain a polynomial-time $(1.4+\epsilon)$-approximation algorithm for Graph Path TSP, improving on a recent $1.497$-approximation algorithm of Traub and Vygen. #R##N#We obtain our results through a variety of new techniques, including a novel way to set up a recursive dynamic program to guess significant parts of an optimal solution. At the core of our dynamic program we deal with instances of a new generalization of (Path) TSP which combines parity constraints with certain connectivity requirements. This problem, which we call $\Phi$-TSP, has a constant-factor approximation algorithm and can be reduced to TSP in certain cases when the dynamic program would not make sufficient progress.

Includes members:
  Member "beating the integrality ratio for s t tours in graphs":
    also connected through other hyperedges:
      (none)
  Member "a 1 5 approximation for path tsp":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "minimum scan cover with angular transition costs")
  Member "better s t tours by gao trees":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "an improved upper bound on the integrality ratio for the s t path tsp")
  Member "reassembling trees for the traveling salesman":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "an improved upper bound on the integrality ratio for the s t path tsp")
  Member "eight fifth approximation for the path tsp":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "constant factor approximation algorithms for parity constrained facility location problems")
  Member "new inapproximability bounds for tsp":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a quasi polynomial algorithm for well spaced hyperbolic tsp")
  Member "approximating minimum cost connected t joins":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "constant factor approximation algorithms for parity constrained facility location problems")
  Member "improving christofides algorithm for the s t path tsp":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a constant factor approximation for directed latency in quasi polynomial time")

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.DM(Discrete Mathematics)