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 "coded computing for distributed graph analytics"):
  Abstract: Many distributed graph computing systems have been developed recently for efficient processing of massive graphs. These systems require many messages to be exchanged among computing machines at each step of the computation, making communication bandwidth a major performance bottleneck. We present a coded computing framework that systematically injects redundancy in the computation phase to enable coding opportunities in the communication phase thus reducing the communication load substantially. Specifically, we propose coded schemes that enable an inverse-linear trade-off (asymptotically) between computation load and average communication load for three popular random graphs -- Erd\"os-R\'enyi (ER), random bi-partite (RB), stochastic block model (SBM). The proposed scheme for ER graph is shown to be optimal asymptotically as the graph size $n\rightarrow \infty$. For finite $n$, we demonstrate via numerical analysis that for a given computation load $r$, i.e. when each graph node is carefully stored at $r$ servers, the proposed scheme slashes the average communication load by (nearly) $r$.

Includes members:
  Member "coded cooperative computation for internet of things":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "adaptive distributed stochastic gradient descent for minimizing delay in the presence of stragglers")
  Member "leveraging coding techniques for speeding up distributed computing":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "parity models a general framework for coding based resilience in ml inference")
  Member "speeding up distributed machine learning using codes":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "gcsa codes with noise alignment for secure coded multi party batch matrix multiplication")
  Member "distributed computing with heterogeneous communication constraints the worst case computation load and proof by contradiction":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "coded distributed computing with heterogeneous function assignments")
  Member "compressed coded distributed computing":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "coded distributed computing schemes with smaller numbers of input files and output functions")
  Member "fundamental limits of coded linear transform":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "gcsa codes with noise alignment for secure coded multi party batch matrix multiplication")
  Member "fundamental resource trade offs for encoded distributed optimization":
    also connected through other hyperedges:
      (none)
  Member "rateless codes for near perfect load balancing in distributed matrix vector multiplication":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "gcsa codes with noise alignment for secure coded multi party batch matrix multiplication")

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)