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: "information theoretic limits of data shuffling for distributed learning"
  Abstract: Data shuffling is one of the fundamental building blocks for distributed learning algorithms, that increases the statistical gain for each step of the learning process. In each iteration, different shuffled data points are assigned by a central node to a distributed set of workers to perform local computations, which leads to communication bottlenecks. The focus of this paper is on formalizing and understanding the fundamental information-theoretic trade-off between storage (per worker) and the worst-case communication overhead for the data shuffling problem. We completely characterize the information theoretic trade-off for $K=2$, and $K=3$ workers, for any value of storage capacity, and show that increasing the storage across workers can reduce the communication overhead by leveraging coding. We propose a novel and systematic data delivery and storage update strategy for each data shuffle iteration, which preserves the structural properties of the storage across the workers, and aids in minimizing the communication overhead in subsequent data shuffling iterations.

Connected through hyperedge HE-1 (induced by source paper "coded distributed computing over packet erasure channels"):
  with members:
    - "speeding up distributed machine learning using codes"
    - "hierarchical coding for distributed computing"
    - "exploitation of stragglers in coded computation"
    - "polynomial codes an optimal design for high dimensional coded matrix multiplication"
    - "latency analysis of coded computation schemes over wireless networks"
    - "coded convolution for parallel and distributed computing within a deadline"
    - "coded fourier transform"
    - "a fundamental tradeoff between computation and communication in distributed computing"

Connected through hyperedge HE-2 (induced by source paper "speeding up distributed machine learning using codes"):
  with members:
    - "a pliable index coding approach to data shuffling"
    - "coded computation over heterogeneous clusters"
    - "short dot computing large linear transforms distributedly using coded short dot products"
    - "minimizing latency for secure distributed computing"
    - "a fundamental tradeoff between computation and communication in distributed computing"
    - "a unified coding framework for distributed computing with straggling servers"
    - "on the worst case communication overhead for distributed data shuffling"
    - "efficient redundancy techniques for latency reduction in cloud systems"

Connected through hyperedge HE-3 (induced by source paper "wireless mapreduce distributed computing"):
  with members:
    - "leveraging coding techniques for speeding up distributed computing"
    - "speeding up distributed machine learning using codes"
    - "federated learning strategies for improving communication efficiency"
    - "distributed computing with heterogeneous communication constraints the worst case computation load and proof by contradiction"
    - "coded computing for distributed graph analytics"
    - "hierarchical coding for distributed computing"
    - "compressed coded distributed computing"
    - "coded distributed computing with node cooperation substantially increases speedup factors"

Connected through hyperedge HE-4 (induced by source paper "near optimal coded data shuffling for distributed learning"):
  with members:
    - "the exact rate memory tradeoff for caching with uncoded prefetching"
    - "speeding up distributed machine learning using codes"
    - "on the fundamental limits of coded data shuffling for distributed learning systems"
    - "a pliable index coding approach to data shuffling"
    - "polynomial codes an optimal design for high dimensional coded matrix multiplication"
    - "low subpacketization schemes for coded caching"
    - "latency analysis of coded computation schemes over wireless networks"
    - "communication vs distributed computation an alternative trade off curve"

Connected through hyperedge HE-5 (induced by source paper "coded computing for distributed graph analytics"):
  with members:
    - "coded cooperative computation for internet of things"
    - "leveraging coding techniques for speeding up distributed computing"
    - "speeding up distributed machine learning using codes"
    - "distributed computing with heterogeneous communication constraints the worst case computation load and proof by contradiction"
    - "compressed coded distributed computing"
    - "fundamental limits of coded linear transform"
    - "fundamental resource trade offs for encoded distributed optimization"
    - "rateless codes for near perfect load balancing in distributed matrix vector multiplication"

Connected through hyperedge HE-6 (induced by source paper "fundamental limits of decentralized data shuffling"):
  with members:
    - "coded distributed computing with heterogeneous function assignments"
    - "cascaded coded distributed computing on heterogeneous networks"
    - "embedded index coding"
    - "the exact rate memory tradeoff for caching with uncoded prefetching"
    - "leveraging coding techniques for speeding up distributed computing"
    - "speeding up distributed machine learning using codes"
    - "storage computation and communication a fundamental tradeoff in distributed computing"
    - "coded computing for distributed graph analytics"

Connected through hyperedge HE-7 (induced by source paper "compressed coded distributed computing"):
  with members:
    - "leveraging coding techniques for speeding up distributed computing"
    - "speeding up distributed machine learning using codes"
    - "straggler mitigation in distributed matrix multiplication fundamental limits and optimal coding"
    - "a pliable index coding approach to data shuffling"
    - "polynomial codes an optimal design for high dimensional coded matrix multiplication"
    - "coding for distributed fog computing"
    - "communication vs distributed computation an alternative trade off curve"
    - "short dot computing large linear transforms distributedly using coded short dot products"

Connected through hyperedge HE-8 (induced by source paper "coded computation over heterogeneous clusters"):
  with members:
    - "speeding up distributed machine learning using codes"
    - "fundamental limits of coded linear transform"
    - "straggler mitigation in distributed matrix multiplication fundamental limits and optimal coding"
    - "on the optimal recovery threshold of coded matrix multiplication"
    - "rateless codes for near perfect load balancing in distributed matrix vector multiplication"
    - "a pliable index coding approach to data shuffling"
    - "polynomial codes an optimal design for high dimensional coded matrix multiplication"
    - "coding for distributed fog computing"

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.IT(Information Theory)