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 polynomial computation for noncolluding coded databases"
  Abstract: We consider private polynomial computation (PPC) over noncolluding coded databases. In such a setting a user wishes to compute a multivariate polynomial of degree at most $g$ over $f$ variables (or messages) stored in multiple databases while revealing no information about the desired polynomial to the databases. We construct two novel PPC schemes, where the first is a generalization of our previous work in private linear computation for coded databases. In this scheme we consider Reed-Solomon coded databases with Lagrange encoding, which leverages ideas from recently proposed star-product private information retrieval and Lagrange coded computation. The second scheme considers the special case of coded databases with systematic Lagrange encoding. Both schemes yield improved rates compared to the best known schemes from the literature for a small number of messages, while in the asymptotic case the rates match.

Connected through hyperedge HE-1 (induced by source paper "on the capacity of private monomial computation"):
  with members:
    - "achievable rate of private function retrieval from mds 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-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"
    - "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"
    - "robust private information retrieval from coded systems with byzantine and colluding servers"

Connected through hyperedge HE-3 (induced by source paper "private inner product retrieval for distributed machine learning"):
  with members:
    - "noisy private information retrieval on separability of channel coding and information retrieval"
    - "capacity of private linear computation for coded databases"
    - "private polynomial computation from lagrange encoding"
    - "fundamental limits of cache aided private information retrieval with unknown and uncoded prefetching"
    - "the capacity of private information retrieval from byzantine and colluding databases"
    - "private function retrieval"
    - "multi message private information retrieval capacity results and near optimal schemes"
    - "the capacity of private computation"

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)