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: "minimizing latency for secure distributed computing"
  Abstract: We consider the setting of a master server who possesses confidential data (genomic, medical data, etc.) and wants to run intensive computations on it, as part of a machine learning algorithm for example. The master wants to distribute these computations to untrusted workers who have volunteered or are incentivized to help with this task. However, the data must be kept private (in an information theoretic sense) and not revealed to the individual workers. The workers may be busy, or even unresponsive, and will take a random time to finish the task assigned to them. We are interested in reducing the aggregate delay experienced by the master. We focus on linear computations as an essential operation in many iterative algorithms. A known solution is to use a linear secret sharing scheme to divide the data into secret shares on which the workers can compute. We propose to use instead new secure codes, called Staircase codes, introduced previously by two of the authors. We study the delay induced by Staircase codes which is always less than that of secret sharing. The reason is that secret sharing schemes need to wait for the responses of a fixed fraction of the workers, whereas Staircase codes offer more flexibility in this respect. For instance, for codes with rate $R=1/2$ Staircase codes can lead to up to $40\%$ reduction in delay compared to secret sharing.

Connected through hyperedge HE-1 (induced by source paper "adaptive distributed stochastic gradient descent for minimizing delay in the presence of stragglers"):
  with members:
    - "coded cooperative computation for internet of things"
    - "speeding up distributed machine learning using codes"
    - "anytime stochastic gradient descent a time to hear from all the workers"
    - "on the optimal recovery threshold of coded matrix multiplication"
    - "lagrange coded computing optimal design for resiliency security and privacy"
    - "exploitation of stragglers in coded computation"
    - "don t decay the learning rate increase the batch size"
    - "short dot computing large linear transforms distributedly using coded short dot products"

Connected through hyperedge HE-2 (induced by source paper "stochastic gradient coding for straggler mitigation in distributed learning"):
  with members:
    - "fundamental limits of approximate gradient coding"
    - "analyzing the download time of availability codes"
    - "distributed stochastic gradient descent using ldgm codes"
    - "erasurehead distributed gradient descent without delays using approximate gradient coding"
    - "coded cooperative computation for internet of things"
    - "speeding up distributed machine learning using codes"
    - "anytime stochastic gradient descent a time to hear from all the workers"
    - "speeding up distributed gradient descent by utilizing non persistent stragglers"

Connected through hyperedge HE-3 (induced by source paper "private and rateless adaptive coded matrix vector multiplication"):
  with members:
    - "codedprivateml a fast and privacy preserving framework for distributed machine learning"
    - "analyzing the download time of availability codes"
    - "secure coded cooperative computation at the heterogeneous edge against byzantine attacks"
    - "an application of storage optimal matdot codes for coded matrix multiplication fast k nearest neighbors estimation"
    - "speeding up distributed machine learning using codes"
    - "anytime stochastic gradient descent a time to hear from all the workers"
    - "gasp codes for secure distributed matrix multiplication"
    - "speeding up distributed gradient descent by utilizing non persistent stragglers"

Connected through hyperedge HE-4 (induced by source paper "on the optimality of d2d coded caching with uncoded cache placement and one shot delivery"):
  with members:
    - "the exact rate memory tradeoff for caching with uncoded prefetching"
    - "speeding up distributed machine learning using codes"
    - "wireless mapreduce distributed computing"
    - "a pliable index coding approach to data shuffling"
    - "coded computation over heterogeneous clusters"
    - "characterizing the rate memory tradeoff in cache networks within a factor of 2"
    - "coded caching in partially cooperative d2d communication networks"
    - "how to optimally allocate resources for coded distributed computing"

Connected through hyperedge HE-5 (induced by source paper "on the upload versus download cost for secure and private matrix multiplication"):
  with members:
    - "distributed and private coded matrix computation with flexible communication load"
    - "private secure coded computation"
    - "achievable rate of private function retrieval from mds coded databases"
    - "gasp codes for secure distributed matrix multiplication"
    - "rate efficiency and straggler robustness through partition in distributed two sided secure matrix computation"
    - "straggler mitigation in distributed matrix multiplication fundamental limits and optimal coding"
    - "on the capacity of secure distributed matrix multiplication"
    - "on the optimal recovery threshold of coded matrix multiplication"

Connected through hyperedge HE-6 (induced by source paper "timely throughput optimal coded computing over cloud networks"):
  with members:
    - "hierarchical coded computation"
    - "speeding up distributed machine learning using codes"
    - "coded computing for distributed graph analytics"
    - "communication aware scheduling of serial tasks for dispersed computing"
    - "lagrange coded computing optimal design for resiliency security and privacy"
    - "coded computation over heterogeneous clusters"
    - "polynomial codes an optimal design for high dimensional coded matrix multiplication"
    - "coding for distributed fog computing"

Connected through hyperedge HE-7 (induced by source paper "secure coded cooperative computation at the heterogeneous edge against byzantine attacks"):
  with members:
    - "speeding up distributed machine learning using codes"
    - "lagrange coded computing optimal design for resiliency security and privacy"
    - "coded computation over heterogeneous clusters"
    - "polynomial codes an optimal design for high dimensional coded matrix multiplication"
    - "coded convolution for parallel and distributed computing within a deadline"
    - "short dot computing large linear transforms distributedly using coded short dot products"
    - "effective straggler mitigation which clones should attack and when"
    - "improving distributed gradient descent using reed solomon codes"

Connected through hyperedge HE-8 (induced by source paper "hcfcontext smartphone context inference via sequential history based collaborative filtering"):
  with members:
    - "anticipatory mobile computing a survey of the state of the art and research challenges"

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)