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 "weighted automata extraction from recurrent neural networks via regression on state spaces"):
  Abstract: We present a method to extract a weighted finite automaton (WFA) from a recurrent neural network (RNN). Our algorithm is based on the WFA learning algorithm by Balle and Mohri, which is in turn an extension of Angluin's classic \lstar algorithm. Our technical novelty is in the use of \emph{regression} methods for the so-called equivalence queries, thus exploiting the internal state space of an RNN to prioritize counterexample candidates. This way we achieve a quantitative/weighted extension of the recent work by Weiss, Goldberg and Yahav that extracts DFAs. We experimentally evaluate the accuracy, expressivity and efficiency of the extracted WFAs.

Includes members:
  Member "state regularized recurrent neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "aging memories generate more fluent dialogue responses with memory networks")
  Member "intrusion prediction with system call sequence to sequence model":
    also connected through other hyperedges:
      (none)
  Member "explaining black boxes on sequential data using weighted automata":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "analyzing recurrent neural network by probabilistic abstraction")
  Member "on the practical computational power of finite precision rnns for language recognition":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "does syntax need to grow on trees sources of hierarchical inductive bias in sequence to sequence networks")
  Member "connecting weighted automata and recurrent neural networks through spectral learning":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "tensor networks for language modeling")
  Member "bisimulation metrics for weighted automata":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a van benthem theorem for fuzzy modal logic")
  Member "extracting automata from recurrent neural networks using queries and counterexamples":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "verifiable rnn based policies for pomdps under temporal logic constraints")
  Member "crafting adversarial input sequences for recurrent neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "robustness verification for transformers")

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)