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 "stealing black box functionality using the deep neural tree architecture"):
  Abstract: This paper makes a substantial step towards cloning the functionality of black-box models by introducing a Machine learning (ML) architecture named Deep Neural Trees (DNTs). This new architecture can learn to separate different tasks of the black-box model, and clone its task-specific behavior. We propose to train the DNT using an active learning algorithm to obtain faster and more sample-efficient training. In contrast to prior work, we study a complex "victim" black-box model based solely on input-output interactions, while at the same time the attacker and the victim model may have completely different internal architectures. The attacker is a ML based algorithm whereas the victim is a generally unknown module, such as a multi-purpose digital chip, complex analog circuit, mechanical system, software logic or a hybrid of these. The trained DNT module not only can function as the attacked module, but also provides some level of explainability to the cloned model due to the tree-like nature of the proposed architecture.

Includes members:
  Member "neural network gradient based learning of black box function interfaces":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "rest performance improvement of a black box model via rl based spatial transformation")
  Member "a survey on explainable artificial intelligence xai towards medical xai":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "neural generators of sparse local linear models for achieving both accuracy and interpretability")
  Member "knockoff nets stealing functionality of black box models":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "dynamic backdoor attacks against machine learning models")
  Member "neural arithmetic logic units":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "neural arithmetic units")
  Member "hyperbolic neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "data augmentation with mobius transformations")
  Member "query efficient black box attack by active learning":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "making targeted black box evasion attacks effective and efficient")
  Member "adaptive neural trees":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "distilled hierarchical neural ensembles with adaptive inference cost")
  Member "stealing hyperparameters in machine learning":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "dynamic backdoor attacks against machine learning models")

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)