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 "a data dependent algorithm for querying earth mover s distance with low doubling dimension"):
  Abstract: In this paper, we consider the following query problem: given two weighted point sets $A$ and $B$ in the Euclidean space $\mathbb{R}^d$, we want to quickly determine that whether their earth mover's distance (EMD) is larger or smaller than a pre-specified threshold $T\geq 0$. The problem finds a number of important applications in the fields of machine learning and data mining. In particular, we assume that the dimensionality $d$ is not fixed and the sizes $|A|$ and $|B|$ are large. Therefore, most of existing EMD algorithms are not quite efficient to solve this problem. Here, we consider the problem under the assumption that $A$ and $B$ have low doubling dimension, which is common for high-dimensional data in real world. Inspired by the geometric method {\em net tree}, we propose a novel "data-dependent" algorithm to solve this problem efficiently. We also study the performance of our method on real datasets, and the experimental results suggest that our method can save a large amount of running time comparing with existing EMD algorithms.

Includes members:
  Member "conditional hardness of earth mover distance":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "scheduling lower bounds via and subset sum")
  Member "near linear time approximation algorithms for optimal transport via sinkhorn iteration":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "geometric dataset distances via optimal transport")
  Member "optimal transport for domain adaptation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "unsupervised multi class domain adaptation theory algorithms and practice")
  Member "a survey on truth discovery":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "joint inference on truth rumor and their sources in social networks")
  Member "on constant factor approximation for earth mover distance over doubling metrics":
    also connected through other hyperedges:
      (none)
  Member "fast construction of nets in low dimensional metrics and their applications":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "distributed construction of light networks")

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)