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: "achievable rate of private function retrieval from mds coded databases"
  Abstract: We study the problem of private function retrieval (PFR) in a distributed storage system. In PFR the user wishes to retrieve a linear combination of  $M$  messages stored in non-colluding (N, K) MDS coded databases while revealing no information about the coefficients of the intended linear combination to any of the individual databases. We present an achievable scheme for MDS coded PFR with a rate that matches the capacity for coded private information retrieval derived recently,  $R= (1+R_{c}+R_{c}^{2}+\cdots +R_{c}^{M-1})^{-1}=\frac{1-R_{c}}{1-R_{c}^{M}}$ , where  $R_{c}=\frac{K}{N}$  is the rate of the MDS code.

Connected through hyperedge HE-1 (induced by source paper "private computation with individual and joint privacy"):
  with members:
    - "on an equivalence between single server pir with side information and locally recoverable codes"
    - "private information retrieval with private coded side information the multi server case"
    - "single server single message online private information retrieval with side information"
    - "single server multi message individually private information retrieval with side information"
    - "the role of coded side information in single server private information retrieval"
    - "multi server private information retrieval with coded side information"
    - "multi message private information retrieval with private side information"
    - "the capacity of private information retrieval with private side information under storage constraints"

Connected through hyperedge HE-2 (induced by source paper "on the capacity of private monomial computation"):
  with members:
    - "private polynomial computation for noncolluding coded databases"
    - "capacity of private linear computation for coded databases"
    - "private computation of systematically encoded data with colluding servers"
    - "private polynomial computation from lagrange encoding"
    - "private function retrieval"
    - "the capacity of private computation"
    - "the capacity of private information retrieval"

Connected through hyperedge HE-3 (induced by source paper "private sequential function computation"):
  with members:
    - "private inner product retrieval for distributed machine learning"
    - "on the capacity of computation broadcast"
    - "private information retrieval with private coded side information the multi server case"
    - "on the asymptotic capacity of x secure t private information retrieval with graph based replicated storage"
    - "private polynomial computation for noncolluding coded databases"
    - "on the upload versus download cost for secure and private matrix multiplication"
    - "private proximity retrieval codes"
    - "robust private information retrieval from coded systems with byzantine and colluding servers"

Connected through hyperedge HE-4 (induced by source paper "on the asymptotic capacity of x secure t private information retrieval with graph based replicated storage"):
  with members:
    - "private information retrieval from coded storage systems with colluding byzantine and unresponsive servers"
    - "cross subspace alignment and the asymptotic capacity of x secure t private information retrieval"
    - "capacity achieving private information retrieval codes with optimal message size and upload cost"
    - "the capacity of private information retrieval with eavesdroppers"
    - "private information retrieval through wiretap channel ii privacy meets security"
    - "private information retrieval in graph based replication systems"
    - "asymmetry hurts private information retrieval under asymmetric traffic constraints"
    - "private computation of systematically encoded data with colluding servers"

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"
    - "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"
    - "lagrange coded computing optimal design for resiliency security and privacy"

Connected through hyperedge HE-6 (induced by source paper "private polynomial computation for noncolluding coded databases"):
  with members:
    - "lifting private information retrieval from two to any number of messages"
    - "capacity of private linear computation for coded databases"
    - "lagrange coded computing optimal design for resiliency security and privacy"
    - "private information retrieval from mds coded data in distributed storage systems"
    - "the asymptotic capacity of private search"
    - "private computation of systematically encoded data with colluding servers"
    - "private polynomial computation from lagrange encoding"
    - "private function retrieval"

Connected through hyperedge HE-7 (induced by source paper "private polynomial computation from lagrange encoding"):
  with members:
    - "codedprivateml a fast and privacy preserving framework for distributed machine learning"
    - "private information retrieval from coded storage systems with colluding byzantine and unresponsive servers"
    - "cross subspace alignment and the asymptotic capacity of x secure t private information retrieval"
    - "one shot pir refinement and lifting"
    - "capacity of private linear computation for coded databases"
    - "lagrange coded computing optimal design for resiliency security and privacy"
    - "private information retrieval from mds coded data in distributed storage systems"
    - "private computation of systematically encoded data with colluding servers"

Connected through hyperedge HE-8 (induced by source paper "capacity of private linear computation for coded databases"):
  with members:
    - "asymmetry helps improved private information retrieval protocols for distributed storage"
    - "an mds pir capacity achieving protocol for distributed storage using non mds linear codes"
    - "on the fundamental limit of private information retrieval for coded distributed storage"
    - "private information retrieval from mds coded data in distributed storage systems"
    - "the asymptotic capacity of private search"
    - "private computation of systematically encoded data with colluding servers"
    - "achieving private information retrieval capacity in distributed storage using an arbitrary linear code"
    - "private function retrieval"

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)