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: "subset typicality lemmas and improved achievable regions in multiterminal source coding"
  Abstract: Consider the following information theoretic setup wherein independent codebooks of N correlated random variables are generated according to their respective marginals. The problem of determining the conditions on the rates of codebooks to ensure the existence of at least one codeword tuple which is jointly typical with respect to a given joint density (called the multivariate covering lemma) has been studied fairly well and the associated rate regions have found applications in several source coding scenarios. However, several multiterminal source coding applications, such as the general multi-user Gray-Wyner network, require joint typicality only within subsets of codewords transmitted. Motivated by such applications, we ask ourselves the conditions on the rates to ensure the existence of at least one codeword tuple which is jointly typical within subsets according to given per subset joint densities. This report focuses primarily on deriving a new achievable rate region for this problem which strictly improves upon the direct extension of the multivariate covering lemma, which has quite popularly been used in several earlier work. Towards proving this result, we derive two important results called `subset typicality lemmas' which can potentially have broader applicability in more general scenarios beyond what is considered in this report. We finally apply the results therein to derive a new achievable region for the general multi-user Gray-Wyner network.

Connected through hyperedge HE-1 (induced by source paper "rate memory trade off for caching and delivery of correlated sources"):
  with members:
    - "the exact rate memory tradeoff for caching with uncoded prefetching"
    - "on coding for cache aided delivery of dynamic correlated content"
    - "broadcast caching networks with two receivers and multiple correlated sources"
    - "optimization of heterogeneous coded caching"
    - "characterizing the rate memory tradeoff in cache networks within a factor of 2"
    - "centralized coded caching of correlated contents"
    - "rate memory trade off for the two user broadcast caching network with correlated sources"
    - "information theoretic caching the multi user case"

Connected through hyperedge HE-2 (induced by source paper "broadcast caching networks with two receivers and multiple correlated sources"):
  with members:
    - "the exact rate memory tradeoff for caching with uncoded prefetching"
    - "characterizing the rate memory tradeoff in cache networks within a factor of 2"
    - "centralized coded caching of correlated contents"
    - "rate memory trade off for the two user broadcast caching network with correlated sources"
    - "information theoretic caching the multi user case"
    - "correlation aware distributed caching and coded delivery"
    - "cache aided coded multicast for correlated sources"
    - "a rate distortion approach to caching"

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)