human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "zeno robust asynchronous sgd with arbitrary number of byzantine workers"
  Abstract: We propose Zeno++, a new robust asynchronous synchronous Stochastic Gradient Descent~(SGD) under a general Byzantine failure model with unbounded number of Byzantine workers.

Connected through hyperedge HE-1 (induced by source paper "towards byzantine resilient learning in decentralized systems"):
  with members:
    - "zeno robust fully asynchronous sgd"
    - "slsgd secure and efficient distributed on device machine learning"
    - "towards federated learning at scale system design"
    - "e2 train training state of the art cnns with over 80 energy savings"
    - "local model poisoning attacks to byzantine robust federated learning"
    - "a little is enough circumventing defenses for distributed learning"
    - "communication compression for decentralized training"
    - "generalized byzantine tolerant sgd"

Connected through hyperedge HE-2 (induced by source paper "basgd buffered asynchronous sgd for byzantine learning"):
  with members:
    - "advances and open problems in federated learning"
    - "byzantine stochastic gradient descent"
    - "federated learning strategies for improving communication efficiency"
    - "byzantine robust distributed learning towards optimal statistical rates"
    - "zeno distributed stochastic gradient descent with suspicion based fault tolerance"
    - "gradient sparsification for communication efficient distributed optimization"
    - "adding vs averaging in distributed primal dual optimization"
    - "deep residual learning for image recognition"

Question: Please tell me which class the center node 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)