human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "private information retrieval with private coded side information the multi server case"):
  Abstract: In this paper, we consider the multi-server setting of Private Information Retrieval with Private Coded Side Information (PIR-PCSI) problem. In this problem, there is a database of $K$ messages whose copies are replicated across $N$ servers, and there is a user who knows a random linear combination of a random subset of $M$ messages in the database as side information. The user wishes to download one message from the servers, while protecting the identities of both the demand message and the messages forming the side information. We assume that the servers know the number of messages forming the user's side information in advance, whereas the indices of these messages and their coefficients in the side information are not known to any of the servers a priori. #R##N#Our goal is to characterize (or derive a lower bound on) the capacity, i.e., the maximum achievable download rate, for the following two settings. In the first setting, the set of messages forming the linear combination available to the user as side information, does not include the user's demanded message. For this setting, we show that the capacity is equal to $\left(1+{1}/{N}+\dots+{1}/{N^{K-M-1}}\right)^{-1}$. In the second setting, the demand message contributes to the linear combination available to the user as side information, i.e., the demand message is one of the messages that form the user's side information. For this setting, we show that the capacity is lower-bounded by $\left(1+{1}/{N}+\dots+{1}/{N^{K-M}}\right)^{-1}$. The proposed achievability schemes and proof techniques leverage ideas from both our recent methods proposed for the single-server PIR-PCSI problem as well as the techniques proposed by Sun and Jafar for multi-server private computation problem.

Includes members:
  Member "single server single message online private information retrieval with side information":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "private computation with individual and joint privacy")
  Member "single server multi message individually private information retrieval with side information":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "private computation with individual and joint privacy")
  Member "multi server private information retrieval with coded side information":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "private computation with individual and joint privacy")
  Member "converse for symmetric multi server single message pir with side information":
    also connected through other hyperedges:
      (none)
  Member "multi message private information retrieval with private side information":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "latent variable private information retrieval")
  Member "single server multi message private information retrieval with side information":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "private computation with individual and joint privacy")
  Member "on the capacity of single server multi message private information retrieval with side information":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "private computation with individual and joint privacy")
  Member "capacity of single server single message private information retrieval with coded side information":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "private computation with individual and joint privacy")

Question: Please tell me which class the source paper 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)