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 "collective decision for open set recognition"):
  Abstract: In open set recognition (OSR), almost all existing methods are designed specially for recognizing individual instances, even these instances are collectively coming in batch. Recognizers in decision either reject or categorize them to some known class using empirically-set threshold. Thus the decision threshold plays a key role. However, the selection for it usually depends on the knowledge of known classes, inevitably incurring risks due to lacking available information from unknown classes. On the other hand, a more realistic OSR system should NOT just rest on a reject decision but should go further, especially for discovering the hidden unknown classes among the reject instances, whereas existing OSR methods do not pay special attention. In this paper, we introduce a novel collective/batch decision strategy with an aim to extend existing OSR for new class discovery while considering correlations among the testing instances. Specifically, a collective decision-based OSR framework (CD-OSR) is proposed by slightly modifying the Hierarchical Dirichlet process (HDP). Thanks to HDP, our CD-OSR does not need to define the decision threshold and can implement the open set recognition and new class discovery simultaneously. Finally, extensive experiments on benchmark datasets indicate the validity of CD-OSR.

Includes members:
  Member "open world learning and application to product classification":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "out of domain detection for natural language understanding in dialog systems")
  Member "learning a neural network based representation for open set recognition":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "recent advances in open set recognition a survey")
  Member "unseen class discovery in open world classification":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "semi supervised class discovery")
  Member "the extreme value machine":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "curriculum labeling self paced pseudo labeling for semi supervised learning")
  Member "doc deep open classification of text documents":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "conditional gaussian distribution learning for open set recognition")
  Member "adversarial robustness softmax versus openmax":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "disentangling adversarial robustness and generalization")
  Member "sparse representation based open set recognition":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "conditional gaussian distribution learning for open set recognition")
  Member "generative openmax for multi class open set classification":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "multi class novelty detection using mix up technique")

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)