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 "the spectral underpinning of word2vec"):
  Abstract: word2vec due to Mikolov \textit{et al.} (2013) is a word embedding method that is widely used in natural language processing. Despite its great success and frequent use, theoretical justification is still lacking. The main contribution of our paper is to propose a rigorous analysis of the highly nonlinear functional of word2vec. Our results suggest that word2vec may be primarily driven by an underlying spectral method. This insight may open the door to obtaining provable guarantees for word2vec. We support these findings by numerical simulations. One fascinating open question is whether the nonlinear properties of word2vec that are not captured by the spectral method are beneficial and, if so, by what mechanism.

Includes members:
  Member "network embedding as matrix factorization unifying deepwalk line pte and node2vec":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "adversarial attacks and defenses on graphs a review and empirical study")
  Member "multiview kernels for low dimensional modeling of seismic events":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "geometry based data generation")
  Member "kernel scaling for manifold learning and classification":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "geometry based data generation")
  Member "word2vec skip gram with negative sampling is a weighted logistic pca":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "what the vec towards probabilistically grounded embeddings")
  Member "graph2vec learning distributed representations of graphs":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "few shot learning on graphs via super classes based on graph spectral measures")
  Member "node2vec scalable feature learning for networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "deep graph matching consensus")
  Member "random walks on context spaces towards an explanation of the mysteries of semantic word embeddings":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "humpty dumpty controlling word meanings via corpus poisoning")
  Member "deepwalk online learning of social representations":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "memory based graph 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.LG(Machine Learning)