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 from storage constrained databases coded caching meets pir"):
  Abstract: Private information retrieval (PIR) allows a user to retrieve a desired message out of $K$ possible messages from $N$ databases without revealing the identity of the desired message. Majority of existing works on PIR assume the presence of replicated databases, each storing all the $K$ messages. In this work, we consider the problem of PIR from storage constrained databases. Each database has a storage capacity of $\mu KL$ bits, where $K$ is the number of messages, $L$ is the size of each message in bits, and $\mu \in [1/N, 1]$ is the normalized storage. In the storage constrained PIR problem, there are two key design questions: a) how to store content across each database under storage constraints; and b) construction of schemes that allow efficient PIR through storage constrained databases. The main contribution of this work is a general achievable scheme for PIR from storage constrained databases for any value of storage. In particular, for any $(N,K)$, with normalized storage $\mu= t/N$, where the parameter $t$ can take integer values $t \in \{1, 2, \ldots, N\}$, we show that our proposed PIR scheme achieves a download cost of $\left(1+ \frac{1}{t}+ \frac{1}{t^{2}}+ \cdots + \frac{1}{t^{K-1}}\right)$. The extreme case when $\mu=1$ (i.e., $t=N$) corresponds to the setting of replicated databases with full storage. For this extremal setting, our scheme recovers the information-theoretically optimal download cost characterized by Sun and Jafar as $\left(1+ \frac{1}{N}+ \cdots + \frac{1}{N^{K-1}}\right)$. For the other extreme, when $\mu= 1/N$ (i.e., $t=1$), the proposed scheme achieves a download cost of $K$. The interesting aspect of the result is that for intermediate values of storage, i.e., $1/N < \mu <1$, the proposed scheme can strictly outperform memory-sharing between extreme values of storage.

Includes members:
  Member "multi file private information retrieval from mds coded databases with colluding servers":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "latent variable private information retrieval")
  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 "the capacity of private information retrieval from byzantine and colluding databases":
    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 "private information retrieval from mds coded data with colluding servers settling a conjecture by freij hollanti et al":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "latent variable private information retrieval")
  Member "private information retrieval with side information":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "gcsa codes with noise alignment for secure coded multi party batch matrix multiplication")
  Member "multi message private information retrieval capacity results and near optimal schemes":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "private set intersection a multi message symmetric private information retrieval perspective")

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)