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 "robust automated human activity recognition and its application to sleep research"):
  Abstract: Human Activity Recognition (HAR) is a powerful tool for understanding human behaviour. Pervasive sensors, such as wearable devices, have an increasing market penetration and generate a tremendous amount of data. The myriad of available clinical and consumer-grade wearables generate a continuous time series of a person's daily physical exertion and rest. Applying HAR to the activity time series can provide new insights by enriching the feature set in health studies, and enhancing the personalisation and effectiveness of health, wellness, and fitness applications. The analyses of complex health behaviours such as sleep, traditionally require a time-consuming manual interpretation by experts. This manual work is necessary due to the erratic periodicity and persistent noisiness of human behaviour. In this paper, we present a robust automated human activity recognition algorithm, which we call RAHAR. We test our algorithm in the application area of sleep research by providing a novel framework for evaluating sleep quality and examining the correlation between the aforementioned and an individual's physical activity. Our results improve the state-of-the-art procedure in sleep research by 15% for area under ROC and by 30% for F1 score on average. However, application of RAHAR is not limited to sleep analysis and can be used for understanding other health problems such as obesity, diabetes, and cardiac diseases.

Includes members:
  Member "expanded parts model for semantic description of humans in still images":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "zero shot object detection")
  Member "rank pooling for action recognition":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "short term temporal convolutional networks for dynamic hand gesture recognition")
  Member "an end to end generative framework for video segmentation and recognition":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a hybrid rnn hmm approach for weakly supervised temporal action segmentation")
  Member "human action recognition using factorized spatio temporal convolutional networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "probabilistic future prediction for video scene understanding")
  Member "a robust and efficient video representation for action recognition":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "short term temporal convolutional networks for dynamic hand gesture recognition")
  Member "action recognition with trajectory pooled deep convolutional descriptors":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "panda a gigapixel level human centric video dataset")
  Member "long term recurrent convolutional networks for visual recognition and description":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "learning spatiotemporal features via video and text pair discrimination")
  Member "learning spatiotemporal features with 3d convolutional networks":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "chameleon a deep learning meta architecture for news recommender systems phd thesis")

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)