human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "hierarchical deep feature learning for decoding imagined speech from eeg"
  Abstract: We propose a mixed deep neural network strategy, incorporating parallel combination of Convolutional (CNN) and Recurrent Neural Networks (RNN), cascaded with deep autoencoders and fully connected layers towards automatic identification of imagined speech from EEG. Instead of utilizing raw EEG channel data, we compute the joint variability of the channels in the form of a covariance matrix that provide spatio-temporal representations of EEG. The networks are trained hierarchically and the extracted features are passed onto the next network hierarchy until the final classification. Using a publicly available EEG based speech imagery database we demonstrate around 23.45% improvement of accuracy over the baseline method. Our approach demonstrates the promise of a mixed DNN approach for complex spatial-temporal classification problems.

Connected through hyperedge HE-1 (induced by source paper "touchless typing using head movement based gestures"):
  with members:
    - "fine grained head pose estimation without keypoints"
    - "efficient eye typing with 9 direction gaze estimation"
    - "sequence to sequence learning as beam search optimization"

Connected through hyperedge HE-2 (induced by source paper "speak your mind towards imagined speech recognition with hierarchical deep learning"):
  with members:
    - "an empirical evaluation of generic convolutional and recurrent networks for sequence modeling"
    - "converting your thoughts to texts enabling brain typing via deep feature learning of eeg signals"
    - "neural networks based eeg speech models"
    - "xgboost a scalable tree boosting system"
    - "wavenet a generative model for raw audio"
    - "adam a method for stochastic optimization"

Connected through hyperedge HE-3 (induced by source paper "eeg to f0 establishing artificial neuro muscular pathway for kinematics based fundamental frequency control"):
  with members:
    - "speak your mind towards imagined speech recognition with hierarchical deep learning"
    - "deep learning the eeg manifold for phonological categorization from active thoughts"
    - "sound stream ii towards real time gesture controlled articulatory sound synthesis"

Connected through hyperedge HE-4 (induced by source paper "deep learning the eeg manifold for phonological categorization from active thoughts"):
  with members:
    - "converting your thoughts to texts enabling brain typing via deep feature learning of eeg signals"
    - "neural networks based eeg speech models"
    - "xgboost a scalable tree boosting system"

Question: Please tell me which class the center node 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)