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 "preprocessing under uncertainty"):
  Abstract: In this work we study preprocessing for tractable problems when part of the input is unknown or uncertain. This comes up naturally if, e.g., the load of some machines or the congestion of some roads is not known far enough in advance, or if we have to regularly solve a problem over instances that are largely similar, e.g., daily airport scheduling with few charter flights. Unlike robust optimization, which also studies settings like this, our goal lies not in computing solutions that are (approximately) good for every instantiation. Rather, we seek to preprocess the known parts of the input, to speed up finding an optimal solution once the missing data is known. #R##N#We present efficient algorithms that given an instance with partially uncertain input generate an instance of size polynomial in the amount of uncertain data that is equivalent for every instantiation of the unknown part. Concretely, we obtain such algorithms for Minimum Spanning Tree, Minimum Weight Matroid Basis, and Maximum Cardinality Bipartite Maxing, where respectively the weight of edges, weight of elements, and the availability of vertices is unknown for part of the input. Furthermore, we show that there are tractable problems, such as Small Connected Vertex Cover, for which one cannot hope to obtain similar results.

Includes members:
  Member "network sparsification for steiner problems on planar and bounded genus graphs":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a relaxation of the directed disjoint paths problem a global congestion metric helps")
  Member "deterministic parameterized connected vertex cover":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "parameterized algorithms for maximum cut with connectivity constraints")
  Member "representative sets and irrelevant vertices new tools for kernelization":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on quasipolynomial multicut mimicking networks and kernelization of multiway cut problems")
  Member "finding small separators in linear time via treewidth reduction":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "fixed parameter tractability of counting small minimum s t cuts")
  Member "computing minimum spanning trees with uncertainty":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "the minimum cost query problem on matroids with uncertainty areas")

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)