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: "private computation of systematically encoded data with colluding servers"
  Abstract: Private Computation (PC), recently introduced by Sun and Jafar, is a generalization of Private Information Retrieval (PIR) in which a user wishes to privately compute an arbitrary function of data stored across several servers. We construct a PC scheme which accounts for server collusion, coded data, and non-linear functions. For data replicated over several possibly colluding servers, our scheme computes arbitrary functions of the data with rate equal to the asymptotic capacity of PIR for this setup. For systematically encoded data stored over colluding servers, we privately compute arbitrary functions of the columns of the data matrix and calculate the rate explicitly for polynomial functions. The scheme is a generalization of previously studied star-product PIR schemes.

Connected through hyperedge HE-1 (induced by source paper "on the capacity of private monomial computation"):
  with members:
    - "private polynomial computation for noncolluding coded databases"
    - "achievable rate of private function retrieval from mds coded databases"
    - "capacity of private linear computation for coded databases"
    - "private polynomial computation from lagrange encoding"
    - "private function retrieval"
    - "the capacity of private computation"
    - "the capacity of private information retrieval"

Connected through hyperedge HE-2 (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"
    - "achievable rate of private function retrieval from mds coded databases"

Connected through hyperedge HE-3 (induced by source paper "on the asymptotic capacity of x secure t private information retrieval with graph based replicated storage"):
  with members:
    - "achievable rate of private function retrieval from mds coded databases"
    - "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"

Connected through hyperedge HE-4 (induced by source paper "private proximity retrieval codes"):
  with members:
    - "capacity of private linear computation for coded databases"
    - "private information retrieval from mds coded data in distributed storage systems"
    - "private polynomial computation from lagrange encoding"
    - "achieving private information retrieval capacity in distributed storage using an arbitrary linear code"
    - "the capacity of private information retrieval from byzantine and colluding databases"
    - "private function retrieval"
    - "linear symmetric private information retrieval for mds coded distributed storage with colluding servers"
    - "the capacity of private computation"

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 "private polynomial computation for noncolluding coded databases"):
  with members:
    - "achievable rate of private function retrieval from mds coded databases"
    - "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 polynomial computation from lagrange encoding"
    - "private function retrieval"

Connected through hyperedge HE-7 (induced by source paper "private information retrieval through wiretap channel ii privacy meets security"):
  with members:
    - "building capacity achieving pir schemes with optimal sub packetization over small fields"
    - "asymmetry hurts private information retrieval under asymmetric traffic constraints"
    - "a general private information retrieval scheme for mds coded databases with colluding servers"
    - "multi file private information retrieval from mds coded databases with colluding servers"
    - "the capacity of private information retrieval with partially known private side information"
    - "fundamental limits of cache aided private information retrieval with unknown and uncoded prefetching"
    - "the capacity of private information retrieval with private side information"
    - "the capacity of cache aided private information retrieval"

Connected through hyperedge HE-8 (induced by source paper "private polynomial computation from lagrange encoding"):
  with members:
    - "codedprivateml a fast and privacy preserving framework for distributed machine learning"
    - "achievable rate of private function retrieval from mds coded databases"
    - "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"

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)