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 "multi instance dynamic ordinal random fields for weakly supervised facial behavior analysis"):
  Abstract: We propose a multi-instance-learning (MIL) approach for weakly supervised learning problems, where a training set is formed by bags (sets of feature vectors or instances) and only labels at bag-level are provided. Specifically, we consider the multi-instance dynamic-ordinal-regression (MI-DOR) setting, where the instance labels are naturally represented as ordinal variables and bags are structured as temporal sequences. To this end, we propose MI dynamic ordinal random fields (MI-DORF). In this paper, we treat instance-labels as temporally dependent latent variables in an undirected graphical model. Different MIL assumptions are modelled via newly introduced high-order potentials relating bag and instance-labels within the energy function of the model. We also extend our framework to address the partially observed MI-DOR problem, where a subset of instance labels is also available during training. We show on the tasks of weakly supervised facial action unit and pain intensity estimation, that the proposed framework outperforms alternative learning approaches. Furthermore, we show that MI-DORF can be employed to reduce the data annotation efforts in this context by large-scale.

Includes members:
  Member "incremental boosting convolutional neural network for facial action unit recognition":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "robust regression via deep negative correlation learning")
  Member "recurrent convolutional neural network regression for continuous pain intensity estimation in video":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "emopain challenge 2020 multimodal pain evaluation from facial and bodily expressions")
  Member "multi instance dynamic ordinal random fields for weakly supervised pain intensity estimation":
    also connected through other hyperedges:
      (none)
  Member "variable state latent conditional random fields for facial expression recognition and action unit detection":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "sewa db a rich database for audio visual emotion and sentiment research in the wild")
  Member "multiple instance learning by discriminative training of markov networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "learning to find common objects across few image collections")
  Member "fast exact inference for recursive cardinality models":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "the limited multi label projection layer")

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.CV(Computer Vision and Pattern Recognition)