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 "cross model convolutional neural network for multiple modality data representation"):
  Abstract: A novel data representation method of convolutional neural net- work (CNN) is proposed in this paper to represent data of different modalities. We learn a CNN model for the data of each modality to map the data of differ- ent modalities to a common space, and regularize the new representations in the common space by a cross-model relevance matrix. We further impose that the class label of data points can also be predicted from the CNN representa- tions in the common space. The learning problem is modeled as a minimiza- tion problem, which is solved by an augmented Lagrange method (ALM) with updating rules of Alternating direction method of multipliers (ADMM). The experiments over benchmark of sequence data of multiple modalities show its advantage.

Includes members:
  Member "stochastic learning of multi instance dictionary for earth mover s distance based histogram comparison":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a novel image tag completion method based on convolutional neural network")
  Member "learning convolutional neural network to maximize pos top performance measure":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "cross domain attribute representation based on convolutional neural network")
  Member "optimizing top precision performance measure of content based image retrieval by learning similarity function":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a novel image tag completion method based on convolutional neural network")
  Member "a novel transfer learning method based on common space mapping and weighted domain matching":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a novel image tag completion method based on convolutional neural network")
  Member "supervised cross modal factor analysis for multiple modal data classification":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "optimizing top precision performance measure of content based image retrieval by learning similarity function")
  Member "multiple kernel multivariate performance learning using cutting plane algorithm":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "optimizing top precision performance measure of content based image retrieval by learning similarity function")
  Member "caffe convolutional architecture for fast feature embedding":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "object detection in optical remote sensing images a survey and a new benchmark")
  Member "a convolutional neural network for modelling sentences":
    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)