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 "analysis of remaining uncertainties and exponents under various conditional r e nyi entropies"):
  Abstract: In this paper, we analyze the asymptotics of the normalized remaining uncertainty of a source when a compressed or hashed version of it and correlated side-information is observed. For this system, commonly known as Slepian-Wolf source coding, we establish the optimal (minimum) rate of compression of the source to ensure that the remaining uncertainties vanish. We also study the exponential rate of decay of the remaining uncertainty to zero when the rate is above the optimal rate of compression. In our study, we consider various classes of random universal hash functions. Instead of measuring remaining uncertainties using traditional Shannon information measures, we do so using two forms of the conditional R\'{e}nyi entropy. Among other techniques, we employ new one-shot bounds and the moments of type class enumerator method for these evaluations. We show that these asymptotic results are generalizations of the strong converse exponent and the error exponent of the Slepian-Wolf problem under maximum \emph{a posteriori} (MAP) decoding.

Includes members:
  Member "uniform random number generation from markov chains non asymptotic and asymptotic analyses":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "operational interpretation of renyi information measures via composite hypothesis testing against product and markov distributions")
  Member "security analysis of varepsilon almost dual universal 2 hash functions smoothing of min entropy versus smoothing of renyi entropy of order 2":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "finite blocklength bounds for wiretap channels")
  Member "asymptotic estimates in information theory with non vanishing error probabilities":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "finite sample analysis of image registration")
  Member "equivocations exponents and second order coding rates under various r enyi information measures":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "the renyi capacity and center")
  Member "asymmetric evaluations of erasure and undetected error probabilities":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "distributed detection with empirically observed statistics")
  Member "list decoding random coding exponents and expurgated exponents":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "mismatched guesswork")
  Member "encoding tasks and renyi entropy":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "asymptotic expansions of smooth r e nyi entropies and their applications")
  Member "secure multiterminal source coding with side information at the eavesdropper":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "privacy aware distributed hypothesis testing")

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)