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: "the capacity of private computation"
  Abstract: We introduce the problem of private computation, comprised of $N$ distributed and non-colluding servers, $K$ independent datasets, and a user who wants to compute a function of the datasets privately, i.e., without revealing which function he wants to compute, to any individual server. This private computation problem is a strict generalization of the private information retrieval (PIR) problem, obtained by expanding the PIR message set (which consists of only independent messages) to also include functions of those messages. The capacity of private computation, $C$, is defined as the maximum number of bits of the desired function that can be retrieved per bit of total download from all servers. We characterize the capacity of private computation, for $N$ servers and $K$ independent datasets that are replicated at each server, when the functions to be computed are arbitrary linear combinations of the datasets. Surprisingly, the capacity, $C=\left(1+1/N+\cdots+1/N^{K-1}\right)^{-1}$, matches the capacity of PIR with $N$ servers and $K$ messages. Thus, allowing arbitrary linear computations does not reduce the communication rate compared to pure dataset retrieval. The same insight is shown to hold even for arbitrary non-linear computations when the number of datasets $K\rightarrow\infty$.

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"
    - "achievable rate of private function retrieval from mds coded databases"
    - "multi message private information retrieval with private side information"

Connected through hyperedge HE-2 (induced by source paper "on optimal load memory tradeoff of cache aided scalar linear function retrieval"):
  with members:
    - "codedprivateml a fast and privacy preserving framework for distributed machine learning"
    - "on coded caching with private demands"
    - "device to device private caching with trusted server"
    - "private and secure distributed matrix multiplication with flexible communication load"
    - "on the optimality of d2d coded caching with uncoded cache placement and one shot delivery"
    - "the exact rate memory tradeoff for caching with uncoded prefetching"
    - "on the fundamental limits of coded data shuffling for distributed learning systems"
    - "near optimal coded data shuffling for distributed learning"

Connected through hyperedge HE-3 (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 computation of systematically encoded data with colluding servers"
    - "private polynomial computation from lagrange encoding"
    - "private function retrieval"
    - "the capacity of private information retrieval"

Connected through hyperedge HE-4 (induced by source paper "private set intersection a multi message symmetric private information retrieval perspective"):
  with members:
    - "the capacity of private information retrieval from heterogeneous uncoded caching databases"
    - "on the storage cost of private information retrieval"
    - "on the information leakage in private information retrieval systems"
    - "capacity achieving private information retrieval codes from mds coded databases with minimum message size"
    - "improved storage for efficient private information retrieval"
    - "staircase pir universally robust private information retrieval"
    - "noisy private information retrieval on separability of channel coding and information retrieval"
    - "the capacity of private information retrieval from uncoded storage constrained databases"

Connected through hyperedge HE-5 (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-6 (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-7 (induced by source paper "on coded caching with private demands"):
  with members:
    - "the exact rate memory tradeoff for caching with uncoded prefetching"
    - "the capacity of private information retrieval from uncoded storage constrained databases"
    - "device to device secure coded caching"
    - "novel inter file coded placement and d2d delivery for a cache aided fog ran architecture"
    - "secrecy capacity memory tradeoff of erasure broadcast channels"
    - "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 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 computation of systematically encoded data with colluding servers"
    - "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"

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)