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 "near optimal linear decision trees for k sum and related problems"):
  Abstract: We construct near optimal linear decision trees for a variety of decision problems in combinatorics and discrete geometry. For example, for any constant $k$, we construct linear decision trees that solve the $k$-SUM problem on $n$ elements using $O(n \log^2 n)$ linear queries. Moreover, the queries we use are comparison queries, which compare the sums of two $k$-subsets; when viewed as linear queries, comparison queries are $2k$-sparse and have only $\{-1,0,1\}$ coefficients. We give similar constructions for sorting sumsets $A+B$ and for solving the SUBSET-SUM problem, both with optimal number of queries, up to poly-logarithmic terms. #R##N#Our constructions are based on the notion of "inference dimension", recently introduced by the authors in the context of active classification with comparison queries. This can be viewed as another contribution to the fruitful link between machine learning and discrete geometry, which goes back to the discovery of the VC dimension.

Includes members:
  Member "generalized comparison trees for point location problems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "noise tolerant reliable active classification with comparison queries")
  Member "active classification with comparison queries":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "efficient active learning of sparse halfspaces with arbitrary bounded noise")
  Member "the decision tree complexity for k sum is at most nearly quadratic":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "fast modular subset sum using linear sketching")
  Member "improved bounds for 3sum k sum and linear degeneracy":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "all non trivial variants of 3 ldt are equivalent")
  Member "clustered integer 3sum via additive combinatorics":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "all non trivial variants of 3 ldt are equivalent")
  Member "solving k sum using few linear queries":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "generalized comparison trees for point location problems")
  Member "threesomes degenerates and love triangles":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "on the fine grained complexity of parity problems")
  Member "higher lower bounds from the 3sum conjecture":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "parallel algorithms for small subgraph counting")

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.CG(Computational Geometry)