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 "modality based factorization for multimodal fusion"):
  Abstract: We propose a multimodal data fusion method by obtaining a $M+1$ dimensional tensor to consider the high-order relationship between $M$ modalities and the output layer of a neural network model. Applying a modality-based tensor factorization method, which adopts different factors for different modalities, results in removing the redundant information with respect to model outputs and leads to fewer model parameters with minimal loss of performance. #R##N#This factorization method works as a regularizer which leads to a less complicated model and avoids overfitting. In addition, a modality-based factorization approach helps to understand the amount of useful information in each modality. #R##N#We have applied this method to three different multimodal datasets in sentiment analysis, personality trait recognition, and emotion recognition. The results demonstrate that the approach yields a 1\% to 4\% improvement on several evaluation measures compared to the state-of-the-art for all three tasks.

Includes members:
  Member "investigating audio visual and text fusion methods for end to end automatic personality prediction":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "modality to modality translation an adversarial representation learning and graph fusion network for multimodal fusion")
  Member "efficient low rank multimodal fusion with modality specific factors":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "h owan multi distorted image restoration with tensor 1x1 convolution")
  Member "tensor fusion network for multimodal sentiment analysis":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "fgn fusion glyph network for chinese named entity recognition")
  Member "multimodal machine learning a survey and taxonomy":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "bert can see out of the box on the cross modal transferability of text representations")
  Member "mosi multimodal corpus of sentiment intensity and subjectivity analysis in online opinion videos":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "gated mechanism for attention based multimodal sentiment analysis")
  Member "adam a method for stochastic optimization":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "using a thousand optimization tasks to learn hyperparameter search strategies")
  Member "medical image fusion a survey of the state of the art":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "vifb a visible and infrared image fusion benchmark")

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)