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: "batched point location in sinr diagrams via algebraic tools"
  Abstract: The SINR model for wireless networks has been extensively studied recently. It tries to model whether a particular transmitter is heard at a specific location, with $n$ transmitting simultaneously. The SINR diagram consists of $n$ regions where each transmitter can be heard and the remaining space where no one can be heard. #R##N#Efficient point location in the SINR diagram, i.e., building a data structure to determine, for a query point, whether any transmitter is heard there, and if so, which one, has been recently investigated. Previous such planar data structures are constructed in time at least quadratic in $n$ and support logarithmic-time approximate queries. Moreover, the performance of these depends not only on the number $n$ of transmitters and on the approximation parameter $\varepsilon$, but also on some geometric parameters that cannot be bounded a priori as a function of $n$ or $\varepsilon$. #R##N#We address the question of batched point location queries, i.e., answering many queries simultaneously. Specifically, in one dimension, we can answer $n$ queries exactly in amortized polylogarithmic time per query, while in the plane we can do it approximately. #R##N#All these results can handle arbitrary power assignments to the transmitters. Moreover, the amortized query time in these results depends only on $n$ and $\varepsilon$. #R##N#We also show how to speed up the preprocessing in a previously proposed point-location structure in SINR diagram for uniform-power sites, by almost a full order of magnitude. For this we obtain results on the sensitivity of the reception regions to slight changes in the reception threshold, which are of independent interest. #R##N#Finally, these results demonstrate the (so far underutilized) power of combining algebraic tools with those of computational geometry and other fields.

Connected through hyperedge HE-1 (induced by source paper "computing shapley values for mean width in 3 d"):
  with members:
    - "computing shapley values in the plane"
    - "on the expected diameter width and complexity of a stochastic convex hull"
    - "epsilon kernel coresets for stochastic points"
    - "convex hulls under uncertainty"

Connected through hyperedge HE-2 (induced by source paper "computing the inverse geodesic length in planar graphs and graphs of bounded treewidth"):
  with members:
    - "minimizing and computing the inverse geodesic length on trees"
    - "voronoi diagrams on planar graphs and computing the diameter in deterministic tilde o n 5 3 time"
    - "subquadratic algorithms for the diameter and the sum of pairwise distances in planar graphs"
    - "structured recursive separator decompositions for planar graphs in linear time"
    - "computing the distance between piecewise linear bivariate functions"

Connected through hyperedge HE-3 (induced by source paper "resolving sinr queries in a dynamic setting"):
  with members:
    - "dynamic geometric data structures via shallow cuttings"
    - "dynamic planar voronoi diagrams for general distance functions and their algorithmic applications"
    - "approximating minimization diagrams and generalized proximity search"
    - "sinr diagram with interference cancellation"
    - "the topology of wireless communication"

Connected through hyperedge HE-4 (induced by source paper "computing shapley values in the plane"):
  with members:
    - "on the separability of stochastic geometric objects with applications"
    - "convex hulls under uncertainty"
    - "area and perimeter of the convex hull of stochastic points"
    - "computing the distance between piecewise linear bivariate functions"

Connected through hyperedge HE-5 (induced by source paper "deterministic digital clustering of wireless ad hoc networks"):
  with members:
    - "a local broadcast layer for the sinr network model"
    - "how well can graphs represent wireless interference"
    - "on the impact of geometry on ad hoc communication in wireless networks"
    - "competitive mac under adversarial sinr"
    - "distributed deterministic broadcasting in uniform power ad hoc wireless networks"
    - "towards tight bounds for local broadcasting"
    - "a constant factor approximation for wireless capacity maximization with power control in the sinr model"
    - "deploying wireless networks with beeps"

Connected through hyperedge HE-6 (induced by source paper "the topology of wireless communication"):
  with members:
    - "wireless capacity with oblivious power in general metrics"
    - "a constant factor approximation for wireless capacity maximization with power control in the sinr model"
    - "sinr diagrams towards algorithmically usable sinr models of wireless networks"

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.CG(Computational Geometry)