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 "enigma ng efficient neural and gradient boosted inference guidance for e"):
  Abstract: We describe an efficient implementation of clause guidance in saturation-based automated theorem provers extending the ENIGMA approach. Unlike in the first ENIGMA implementation where fast linear classifier is trained and used together with manually engineered features, we have started to experiment with more sophisticated state-of-the-art machine learning methods such as gradient boosted trees and recursive neural networks. In particular the latter approach poses challenges in terms of efficiency of clause evaluation, however, we show that deep integration of the neural evaluation with the ATP data-structures can largely amortize this cost and lead to competitive real-time results. Both methods are evaluated on a large dataset of theorem proving problems and compared with the previous approaches. The resulting methods improve on the manually designed clause guidance, providing the first practically convincing application of gradient-boosted and neural clause guidance in saturation-style automated theorem provers.

Includes members:
  Member "atpboost learning premise selection in binary setting with atp feedback":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "guiding theorem proving by recurrent neural networks")
  Member "reinforcement learning of theorem proving":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "an experimental study of formula embeddings for automated theorem proving in first order logic")
  Member "proofwatch watchlist guidance for large theories in e":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a survey on theorem provers in formal methods")
  Member "enigma efficient learning based inference guiding machine":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "an experimental study of formula embeddings for automated theorem proving in first order logic")
  Member "deep network guided proof search":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "teaching temporal logics to neural networks")
  Member "monte carlo tableau proof search":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "hammering mizar by learning clause guidance")
  Member "deepmath deep sequence models for premise selection":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "an experimental study of formula embeddings for automated theorem proving in first order logic")
  Member "xgboost a scalable tree boosting system":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "monotonic cardinality estimation of similarity selection a deep learning approach")

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.AI(Artificial Intelligence)