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 "revisiting skip gram negative sampling model with regularization"):
  Abstract: We revisit skip-gram negative sampling (SGNS), a popular neural-network based approach to learning distributed word representation. We first point out the ambiguity issue undermining the SGNS model, in the sense that the word vectors can be entirely distorted without changing the objective value. To resolve this issue, we rectify the SGNS model with quadratic regularization. A theoretical justification, which provides a novel insight into quadratic regularization, is presented. Preliminary experiments are also conducted on Google's analytical reasoning task to support the modified SGNS model.

Includes members:
  Member "on the convergence of adam and beyond":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "disentangling adaptive gradient methods from learning rates")
  Member "understanding composition of word embeddings via tensor decomposition":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "convergence of end to end training in deep unsupervised contrasitive learning")
  Member "riemannian optimization for skip gram negative sampling":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "rotations and interpretability of word embeddings the case of the russian language")
  Member "advances in pre training distributed word representations":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "multi simlex a large scale evaluation of multilingual and cross lingual lexical semantic similarity")
  Member "word2vec skip gram with negative sampling is a weighted logistic pca":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "the spectral underpinning of word2vec")
  Member "a simple regularization based algorithm for learning cross domain word embeddings":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "benchmark performance of machine and deep learning based methodologies for urdu text document classification")
  Member "greedy approaches to symmetric orthogonal tensor decomposition":
    also connected through other hyperedges:
      (none)
  Member "neural architectures for named entity recognition":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "knowledge graphs")

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.CL(Computation and Language)