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 matrix multiplication on a group based model"):
  Abstract: Coded distributed computing has been considered as a promising technique which makes large-scale systems robust to the "straggler" workers. Yet, practical system models for distributed computing have not been available that reflect the clustered or grouped structure of real-world computing servers. Neither the large variations in the computing power and bandwidth capabilities across different servers have been properly modeled. We suggest a group-based model to reflect practical conditions and develop an appropriate coding scheme for this model. The suggested code, called group code, employs parallel encoding for each group. We show that the suggested coding scheme can asymptotically achieve optimal computing time in regimes of infinite n, the number of workers. While theoretical analysis is conducted in the asymptotic regime, numerical results also show that the suggested scheme achieves near-optimal computing time for any finite but reasonably large n. Moreover, we demonstrate that the decoding complexity of the suggested scheme is significantly reduced by the virtue of parallel decoding.

Includes members:
  Member "speeding up distributed machine learning using codes":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "gcsa codes with noise alignment for secure coded multi party batch matrix multiplication")
  Member "hierarchical coding for distributed computing":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "gcsa codes with noise alignment for secure coded multi party batch matrix multiplication")
  Member "coded computation over heterogeneous clusters":
    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 "polynomial codes an optimal design for high dimensional coded matrix multiplication":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "gcsa codes with noise alignment for secure coded multi party batch matrix multiplication")
  Member "coded convolution for parallel and distributed computing within a deadline":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "gcsa codes with noise alignment for secure coded multi party batch matrix multiplication")
  Member "short dot computing large linear transforms distributedly using coded short dot products":
    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 "gradient coding from cyclic mds codes and expander graphs":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a locality based approach for coded computation")
  Member "improving distributed gradient descent using reed solomon codes":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "a locality based approach for coded computation")

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.IT(Information Theory)