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: "active user authentication for smartphones a challenge data set and benchmark results"
  Abstract: In this paper, automated user verification techniques for smartphones are investigated. A unique non-commercial dataset, the University of Maryland Active Authentication Dataset 02 (UMDAA-02) for multi-modal user authentication research is introduced. This paper focuses on three sensors — front camera, touch sensor and location service while providing a general description for other modalities. Benchmark results for face detection, face verification, touch-based user identification and location-based next-place prediction are presented, which indicate that more robust methods fine-tuned to the mobile platform are needed to achieve satisfactory verification accuracy. The dataset will be made available to the research community for promoting additional research.

Connected through hyperedge HE-1 (induced by source paper "on the resilience of biometric authentication systems against random inputs"):
  with members:
    - "certified adversarial robustness via randomized smoothing"
    - "explainable black box attacks against model based authentication"
    - "ml leaks model and data independent membership inference attacks and defenses on machine learning models"
    - "voxceleb2 deep speaker recognition"
    - "vggface2 a dataset for recognising faces across pose and age"
    - "classification regions of deep neural networks"
    - "voxceleb a large scale speaker identification dataset"
    - "tacotron towards end to end speech synthesis"

Connected through hyperedge HE-2 (induced by source paper "be captcha detecting human behavior in smartphone interaction using multiple inbuilt sensors"):
  with members:
    - "multilock mobile active authentication based on multiple biometric and behavioral patterns"
    - "actions speak louder than pass words passive authentication of smartphone users via deep temporal features"
    - "hacking google recaptcha v3 using reinforcement learning"
    - "mobiface a novel dataset for mobile face tracking in the wild"
    - "continuous authentication of smartphones based on application usage"
    - "path person authentication using trace histories"
    - "the partially observable hidden markov model and its application to keystroke dynamics"
    - "touchalytics on the applicability of touchscreen input as a behavioral biometric for continuous authentication"

Connected through hyperedge HE-3 (induced by source paper "learning deep features for one class classification"):
  with members:
    - "one class convolutional neural network"
    - "active authentication using an autoencoder regularized cnn based one class classifier"
    - "deep transfer learning for multiple class novelty detection"
    - "ocgan one class novelty detection using gans with constrained latent representations"
    - "latent space autoregression for novelty detection"
    - "and autoregressive novelty detectors"
    - "anomaly detection using one class neural networks"
    - "sparse representation based open set recognition"

Connected through hyperedge HE-4 (induced by source paper "one class convolutional neural network"):
  with members:
    - "learning deep features for one class classification"
    - "adversarially learned one class classifier for novelty detection"
    - "and autoregressive novelty detectors"
    - "anomaly detection using one class neural networks"
    - "robust deep and inductive anomaly detection"
    - "abnormal event detection in videos using generative adversarial nets"
    - "improved techniques for training gans"
    - "a learned representation for artistic style"

Connected through hyperedge HE-5 (induced by source paper "active authentication using an autoencoder regularized cnn based one class classifier"):
  with members:
    - "one class convolutional neural network"
    - "learning deep features for one class classification"
    - "adversarially learned one class classifier for novelty detection"
    - "anomaly detection using one class neural networks"
    - "abnormal event detection in videos using generative adversarial nets"
    - "convolutional neural networks for attribute based active authentication on mobile devices"
    - "a learned representation for artistic style"
    - "adam a method for stochastic optimization"

Connected through hyperedge HE-6 (induced by source paper "actions speak louder than pass words passive authentication of smartphone users via deep temporal features"):
  with members:
    - "multilock mobile active authentication based on multiple biometric and behavioral patterns"
    - "active authentication on mobile devices via stylometry application usage web browsing and gps location"
    - "learning human identity from motion patterns"
    - "hmog new behavioral biometric features for continuous authentication of smartphone users"
    - "adam a method for stochastic optimization"
    - "an hmm based behavior modeling approach for continuous mobile authentication"
    - "touchalytics on the applicability of touchscreen input as a behavioral biometric for continuous authentication"

Connected through hyperedge HE-7 (induced by source paper "smartphone multi modal biometric authentication database and evaluation"):
  with members:
    - "mobibits multimodal mobile biometric database"
    - "voxceleb a large scale speaker identification dataset"
    - "facenet a unified embedding for face recognition and clustering"
    - "face anti spoofing based on color texture analysis"

Connected through hyperedge HE-8 (induced by source paper "the mobile ar sensor logger for android and ios devices"):
  with members:
    - "collaborative large scale dense 3d reconstruction with online inter agent pose optimisation"
    - "advio an authentic dataset for visual inertial odometry"
    - "vins mono a robust and versatile monocular visual inertial state estimator"
    - "oxiod the dataset for deep inertial odometry"

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.CV(Computer Vision and Pattern Recognition)