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: "an optimal iterative placement algorithm for pir from heterogeneous storage constrained databases"
  Abstract: We study private information retrieval (PIR) where a user privately downloads one of $K$ messages from $N$ databases (DBs) such that no DB can infer which message is being downloaded. Moreover, we consider the general case where DBs are storage constrained such that DB$_n$ can only store a $\mu[n]KL$ symbols where $0\leq \mu[n] \leq 1$ and $L$ is the number of symbols per message. Let $t= \sum_{n=1}^{N}\mu[n]$ be an integer, a recent work by Banawan et al. showed that the capacity of heterogeneous Storage Constrained PIR (SC-PIR) is $\left( 1+ \frac{1}{t} + \frac{1}{t^2} + \cdots + \frac{1}{t^{K-1}} \right)^{-1}$. However, an achievable, capacity achieving scheme was only developed for a network of $N=3$ DBs. In this paper, we propose an iterative placement algorithm for arbitrary $N$ which achieves heterogeneous SC-PIR capacity when $t$ is an integer. The algorithm defines storage contents of the DBs by assigning sets of sub-messages to $t$ DBs in each iteration. We show that the proposed placement algorithm converges within $N$ iterations and the storage placement requires at most $N$ sub-messages per message without considering the sub-message requirement for the delivery. Finally, we show that the proposed solution can be applied to the case of non-integer $t$ while still achieving capacity.

Connected through hyperedge HE-1 (induced by source paper "heterogeneous computation assignments in coded elastic computing"):
  with members:
    - "optimizing the transition waste in coded elastic computing"
    - "speeding up distributed machine learning using codes"
    - "coded elastic computing"
    - "straggler mitigation in distributed matrix multiplication fundamental limits and optimal coding"
    - "near optimal coded data shuffling for distributed learning"
    - "a fundamental tradeoff between computation and communication in distributed computing"

Connected through hyperedge HE-2 (induced by source paper "breaking the mds pir capacity barrier via joint storage coding"):
  with members:
    - "the capacity of private information retrieval from heterogeneous uncoded caching databases"
    - "capacity achieving private information retrieval codes from mds coded databases with minimum message size"
    - "the capacity of private information retrieval from uncoded storage constrained databases"
    - "batch and pir codes and their connections to locally repairable codes"
    - "on the fundamental limit of private information retrieval for coded distributed storage"
    - "private information retrieval from mds coded data in distributed storage systems"
    - "on sub packetization and access number of capacity achieving pir schemes for mds coded non colluding servers"
    - "private information retrieval from mds coded data with colluding servers settling a conjecture by freij hollanti et al"

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)