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 "on geometric structure of activation spaces in neural networks"):
  Abstract: In this paper, we investigate the geometric structure of activation spaces of fully connected layers in neural networks and then show applications of this study. We propose an efficient approximation algorithm to characterize the convex hull of massive points in high dimensional space. Based on this new algorithm, four common geometric properties shared by the activation spaces are concluded, which gives a rather clear description of the activation spaces. We then propose an alternative classification method grounding on the geometric structure description, which works better than neural networks alone. Surprisingly, this data classification method can be an indicator of overfitting in neural networks. We believe our work reveals several critical intrinsic properties of modern neural networks and further gives a new metric for evaluating them.

Includes members:
  Member "on generalization error bounds of noisy gradient methods for non convex learning":
    also connected through other hyperedges:
      (none)
  Member "communitygan community detection with generative adversarial nets":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "sampled in pairs and driven by text a new graph embedding framework")
  Member "acekg a large scale knowledge graph for academic data mining":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "exploring scholarly data by semantic query on knowledge graph embedding space")
  Member "towards understanding learning representations to what extent do different neural networks learn the same representation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "emerging cross lingual structure in pretrained language models")
  Member "curvature based comparison of two neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "intrinsic dimension of data representations in deep neural networks")
  Member "computing the approximate convex hull in high dimensions":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "semantic explanations of predictions")
  Member "deep learning in neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "π nets deep polynomial neural networks")
  Member "deepwalk online learning of social representations":
    also connected through other hyperedges:
      - Hyperedge HE-7 (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)