human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "violator spaces structure and algorithms"
  Abstract: Sharir and Welzl introduced an abstract framework for optimization problems, called LP-type problems or also generalized linear programming problems, which proved useful in algorithm design. We define a new, and as we believe, simpler and more natural framework: violator spaces, which constitute a proper generalization of LP-type problems. We show that Clarkson's randomized algorithms for low-dimensional linear programming work in the context of violator spaces. For example, in this way we obtain the fastest known algorithm for the P-matrix generalized linear.#R##N##R##N#complementarity problem with a constant number of blocks. We also give two new characterizations of LP-type problems: they are equivalent to acyclic violator spaces, as well as to concrete LP-type problems (informally, the constraints in a concrete LP-type problem are subsets of a linearly ordered ground set, and the value of a set of constraints is the minimum of its intersection).

Connected through hyperedge HE-1 (induced by source paper "fast distributed algorithms for lp type problems of bounded dimension"):
  with members:
    - "optimal gossip algorithms for exact and approximate quantile computations"
    - "analyzing network coding gossip made easy"
    - "local computation lower and upper bounds"
    - "approximating max min linear programs with local algorithms"

Connected through hyperedge HE-2 (induced by source paper "property testing of lp type problems"):
  with members:
    - "testing assignments to constraint satisfaction problems"
    - "clarksons algorithm for violator spaces"

Connected through hyperedge HE-3 (induced by source paper "computational geometry column 67"):
  with members:
    - "common tangents of two disjoint polygons in linear time and constant workspace"
    - "time space trade off for finding the k visibility region of a point in a polygon"
    - "an experimental study of algorithms for geodesic shortest paths in the constant workspace model"
    - "improved time space trade offs for computing voronoi diagrams"
    - "ime space trade offs for computing euclidean minimum spanning trees"
    - "time space trade offs for triangulations and voronoi diagrams"
    - "experimental study of compressed stack algorithms in limited memory environments"
    - "outer common tangents and nesting of convex hulls in linear time and constant workspace"

Connected through hyperedge HE-4 (induced by source paper "constant factor approximation for tsp with disks"):
  with members:
    - "a ptas for tsp with neighborhoods among fat regions in the plane"
    - "the traveling salesman problem low dimensionality implies a polynomial time approximation scheme"
    - "the traveling salesman problem for lines balls and planes"
    - "the guillotine approach for tsp with neighborhoods revisited"
    - "improved approximation algorithms for geometric set cover"
    - "approximation algorithms for tsp with neighborhoods in the plane"

Connected through hyperedge HE-5 (induced by source paper "random sampling in computational algebra helly numbers and violator spaces"):
  with members:
    - "exploiting chordal structure in polynomial ideals a grobner bases approach"
    - "sparse grobner bases the unmixed case"
    - "gr obner bases and nullstellens atze for graph coloring ideals"
    - "polynomial systems solving by fast linear algebra"
    - "clarksons algorithm for violator spaces"

Connected through hyperedge HE-6 (induced by source paper "shortest path in a polygon using sublinear space"):
  with members:
    - "from proximity to utility a voronoi partition of pareto optima"
    - "quasi polynomial time approximation scheme for sparse subsets of polygons"
    - "memory constrained algorithms for simple polygons"

Question: Please tell me which class the center node 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)