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 "subspace aware index codes"):
  Abstract: In this paper, we generalize the well-known index coding problem to exploit the structure in the source-data to improve system throughput. In many applications, the data to be transmitted may lie (or can be well approximated) in a low-dimensional subspace. We exploit this low-dimensional structure of the data using an algebraic framework to solve the index coding problem (referred to as subspace-aware index coding) as opposed to the traditional index coding problem which is subspace-unaware. Also, we propose an efficient algorithm based on the alternating minimization approach to obtain near optimal index codes for both subspace-aware and -unaware cases. Our simulations indicate that under certain conditions, a significant throughput gain (about 90%) can be achieved by subspace-aware index codes over conventional subspace-unaware index codes.

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 "a sparse and low rank optimization framework for index coding via riemannian optimization":
    also connected through other hyperedges:
      (none)
  Member "index coding and network coding via rank minimization":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "preserving privacy while broadcasting k limited access schemes")
  Member "index coding with coded side information":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "code equivalences between network codes with link errors and index codes with side information errors")
  Member "caching and coded multicasting multiple groupcast index coding":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "decentralized asynchronous coded caching design and performance analysis in fog radio access networks")
  Member "quasi linear network coding":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "index coding and network coding via rank minimization")
  Member "rank minimization over finite fields fundamental limits and coding theoretic interpretations":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "almost everywhere injectivity conditions for the matrix recovery problem")
  Member "an equivalence between network coding and index coding":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "embedded index coding")

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)