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 "capacity achieving pir schemes with optimal sub packetization"):
  Abstract: Suppose a database containing $M$ records is replicated across $N$ servers, and a user wants to privately retrieve one record by accessing the servers such that identity of the retrieved record is secret against any up to $T$ servers. A scheme designed for this purpose is called a private information retrieval (PIR) scheme. In practice, capacity-achieving and small sub-packetization are both desired for PIR schemes, because the former implies the highest download rate and the latter usually means simple realization. #R##N#For general values of $N,T,M$, the only known capacity-achieving PIR scheme was designed by Sun and Jafar in 2016 with sub-packetization $N^M$. In this paper, we design a linear capacity-achieving PIR scheme with much smaller sub-packetization $dn^{M-1}$, where $d={\rm gcd}(N,T)$ and $n=N/d$. Furthermore, we prove that for any linear capacity-achieving PIR scheme it must have sub-packetization no less than $dn^{M-1}$, implying our scheme has the optimal sub-packetization. Moreover, comparing with Sun and Jafar's scheme, our scheme reduces the field size by a factor of $\frac{1}{Nd^{M-2}}$.

Includes members:
  Member "the capacity of private information retrieval from byzantine and colluding databases":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "gcsa codes with noise alignment for secure coded multi party batch matrix multiplication")
  Member "the capacity of robust private information retrieval with colluding databases":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "gcsa codes with noise alignment for secure coded multi party batch matrix multiplication")
  Member "the capacity of symmetric private information retrieval":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "latent variable private information retrieval")
  Member "the capacity of private information retrieval":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "gcsa codes with noise alignment for secure coded multi party batch matrix multiplication")
  Member "symmetric private information retrieval for mds coded distributed storage":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "latent variable private information retrieval")
  Member "optimal download cost of private information retrieval for arbitrary message length":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "latent variable private information retrieval")
  Member "private information retrieval for coded storage":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "the capacity of single server weakly private information retrieval")
  Member "an improved sub packetization bound for minimum storage regenerating codes":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "convertible codes efficient conversion of coded data in distributed storage")

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)