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 "overcoming catastrophic forgetting by generative regularization"):
  Abstract: In this paper, we propose a new method to overcome catastrophic forgetting by adding generative regularization to Bayesian inference framework. We could construct generative regularization term for all given models by leveraging Energy-based models and Langevin-Dynamic sampling. By combining discriminative and generative loss together, we show that this intuitively provides a better posterior formulation in Bayesian inference. Experimental results show that the proposed method outperforms state of-the-art methods on a variety of tasks, avoiding catastrophic forgetting in continual learning. In particular, the proposed method outperforms previous methos over 10$\%$ in Fashion-MNIST dataset.

Includes members:
  Member "learn to grow a continual structure learning framework for overcoming catastrophic forgetting":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a neural dirichlet process mixture model for task free continual learning")
  Member "exponential family estimation via adversarial dynamics embedding":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "reinforcement learning via fenchel rockafellar duality")
  Member "supportnet solving catastrophic forgetting in class incremental learning with support data":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "frosting weights for better continual training")
  Member "progressive neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "review analyze and design a comprehensive deep reinforcement learning framework")
  Member "lifelong learning with dynamically expandable networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "online fast adaptation and knowledge accumulation a new approach to continual learning")
  Member "continual learning with deep generative replay":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "online fast adaptation and knowledge accumulation a new approach to continual learning")
  Member "continual learning through synaptic intelligence":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "incremental object detection via meta learning")
  Member "overcoming catastrophic forgetting by incremental moment matching":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "ternary feature masks continual learning without any forgetting")

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)