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 "operational interpretation of renyi information measures via composite hypothesis testing against product and markov distributions"):
  Abstract: We revisit the problem of asymmetric binary hypothesis testing against a composite alternative hypothesis. We introduce a general framework to treat such problems when the alternative hypothesis adheres to certain axioms. In this case, we find the threshold rate, the optimal error and strong converse exponents (at large deviations from the threshold), and the second order asymptotics (at small deviations from the threshold). We apply our results to find the operational interpretations of various Renyi information measures. In case the alternative hypothesis is comprised of bipartite product distributions, we find that the optimal error and strong converse exponents are determined by the variations of Renyi mutual information. In case the alternative hypothesis consists of tripartite distributions satisfying the Markov property, we find that the optimal exponents are determined by the variations of Renyi conditional mutual information. In either case, the relevant notion of Renyi mutual information depends on the precise choice of the alternative hypothesis. As such, this paper also strengthens the view that different definitions of Renyi mutual information, conditional entropy, and conditional mutual information are adequate depending on the context in which the measures are used.

Includes members:
  Member "secure multiplex coding with dependent and non uniform multiple messages":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "exact exponent for soft covering")
  Member "two measures of dependence":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "transportation proofs of r enyi entropy power inequalities")
  Member "uniform random number generation from markov chains non asymptotic and asymptotic analyses":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on privacy amplification lossy compression and their duality to channel coding")
  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 "universal channel coding for exponential family of channels":
    also connected through other hyperedges:
      (none)
  Member "universal channel coding for general output alphabet":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "minimax r enyi redundancy")
  Member "converses for secret key agreement and secure computing":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "biometric and physical identifiers with correlated noise for controllable private authentication")
  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")

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)