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 "layer flexible adaptive computational time for recurrent neural networks"):
  Abstract: Deep recurrent neural networks perform well on sequence data and are the model of choice. It is a daunting task to decide the number of layers, especially considering different computational needs for tasks within a sequence of different difficulties. We propose a layer flexible recurrent neural network with adaptive computational time, and expand it to a sequence to sequence model. Contrary to the adaptive computational time model, our model has a dynamic number of transmission states which vary by step and sequence. We evaluate the model on a financial data set and Wikipedia language modeling. Experimental results show the performance improvement of 2% to 3% and indicate the model's ability to dynamically change the number of layers.

Includes members:
  Member "universal transformers":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "train large then compress rethinking model size for efficient training and inference of transformers")
  Member "depth adaptive computational policies for efficient visual tracking":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "looking fast and slow memory guided mobile video object detection")
  Member "dynamic prediction length for time series with sequence to sequence networks":
    also connected through other hyperedges:
      (none)
  Member "iamnn iterative and adaptive mobile neural network for efficient image classification":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "extd extremely tiny face detector via iterative filter reuse")
  Member "early improving recurrent elastic highway network":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "relaxed weight sharing effectively modeling time varying relationships in clinical time series")
  Member "learning to skim text":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "memo a deep network for flexible combination of episodic memories")
  Member "dynamic computational time for visual attention":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "channel interaction networks for fine grained image categorization")
  Member "learning to reason with adaptive computation":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "constructing datasets for multi hop reading comprehension across documents")

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)