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 "on sub packetization of capacity achieving pir schemes for mds coded databases"):
  Abstract: Consider the problem of private information retrieval (PIR) over a distributed storage system where $M$ records are stored across $N$ servers by using an $[N,K]$ MDS code. For simplicity, this problem is usually referred as the coded-PIR problem. The capacity of coded-PIR with privacy against any individual server was determined by Banawan and Ulukus in 2016, i.e., $\mathcal{C}_{\tiny C-PIR}=(1+\frac{K}{N}+\dots+\frac{K^{M-1}}{N^{M-1}})^{-1}$. They also presented a linear capacity-achieving scheme with sub-packetization $KN^{M}$. In this paper we focus on minimizing the sub-packetization for linear capacity-achieving coded-PIR schemes. We prove that the sub-packetization for all linear capacity-achieving coded-PIR schemes in the nontrivial cases (i.e. $N>K\geq 1$ and $M>1$) must be no less than $Kn^{M-1}$, where $n=N/{\rm gcd}(N,K)$. Moreover, we design a linear capacity-achieving coded-PIR scheme with sub-packetization $Kn^{M-1}$ for all $N>K\geq 1$ and $M>1$. Therefore, $Kn^{M-1}$ is the optimal sub-packetization for linear capacity-achieving coded-PIR schemes.

Includes members:
  Member "a general private information retrieval scheme for mds coded databases with colluding servers":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "private set intersection a multi message symmetric private information retrieval perspective")
  Member "fundamental limits of cache aided private information retrieval with unknown and uncoded prefetching":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "latent variable private information retrieval")
  Member "the capacity of private information retrieval with private side information":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "private computation with individual and joint privacy")
  Member "the capacity of cache aided private information retrieval":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "latent variable private information retrieval")
  Member "private information retrieval with side information":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "gcsa codes with noise alignment for secure coded multi party batch matrix multiplication")
  Member "capacity achieving pir schemes with optimal sub packetization":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "towards the capacity of private information retrieval from coded and colluding servers")
  Member "a tight lower bound on the sub packetization level of optimal access msr and mds codes":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "towards practical private information retrieval from mds array codes")
  Member "the capacity of robust private information retrieval with colluding databases":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "gcsa codes with noise alignment for secure coded multi party batch matrix multiplication")

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)