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 "randomized reactive redundancy for byzantine fault tolerance in parallelized learning"):
  Abstract: This report considers the problem of Byzantine fault-tolerance in synchronous parallelized learning that is founded on the parallelized stochastic gradient descent (parallelized-SGD) algorithm. The system comprises a master, and $n$ workers, where up to $f$ of the workers are Byzantine faulty. Byzantine workers need not follow the master's instructions correctly, and might send malicious incorrect (or faulty) information. The identity of the Byzantine workers remains fixed throughout the learning process, and is unknown a priori to the master. We propose two coding schemes, a deterministic scheme and a randomized scheme, for guaranteeing exact fault-tolerance if $2f < n$. The coding schemes use the concept of reactive redundancy for isolating Byzantine workers that eventually send faulty information. We note that the computation efficiencies of the schemes compare favorably with other (deterministic or randomized) coding schemes, for exact fault-tolerance.

Includes members:
  Member "doublesqueeze parallel stochastic gradient descent with double pass error compensated compression":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "gradient sparification for asynchronous distributed training")
  Member "detox a redundancy based framework for faster and more robust gradient aggregation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "salvaging federated learning by local adaptation")
  Member "byzantine fault tolerant distributed linear regression":
    also connected through other hyperedges:
      (none)
  Member "fast machine learning with byzantine workers and servers":
    also connected through other hyperedges:
      (none)
  Member "byzantine robust distributed learning towards optimal statistical rates":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "turbo aggregate breaking the quadratic aggregation barrier in secure federated learning")
  Member "sever a robust meta algorithm for stochastic optimization":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "on the effectiveness of mitigating data poisoning attacks with gradient shaping")
  Member "signsgd compressed optimisation for non convex problems":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "communication optimization strategies for distributed deep learning a survey")
  Member "sparse communication for distributed gradient descent":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "communication optimization strategies for distributed deep learning a survey")

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.DC(Distributed, Parallel, and Cluster Computing)