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 "first and second order hypothesis testing for mixed memoryless sources"):
  Abstract: The first- and second-order optimum achievable exponents in the simple hypothesis testing problem are investigated. The optimum achievable exponent for type II error probability, under the constraint that the type I error probability is allowed asymptotically up to #R##N#          #R##N#            #R##N#              e#R##N#            #R##N#          #R##N#        , is called the #R##N#          #R##N#            #R##N#              e#R##N#            #R##N#          #R##N#        -optimum exponent. In this paper, we first give the second-order #R##N#          #R##N#            #R##N#              e#R##N#            #R##N#          #R##N#        -optimum exponent in the case where the null hypothesis and alternative hypothesis are a mixed memoryless source and a stationary memoryless source, respectively. We next generalize this setting to the case where the alternative hypothesis is also a mixed memoryless source. Secondly, we address the first-order #R##N#          #R##N#            #R##N#              e#R##N#            #R##N#          #R##N#        -optimum exponent in this setting. In addition, an extension of our results to the more general setting such as hypothesis testing with mixed general source and a relationship with the general compound hypothesis testing problem are also discussed.

Includes members:
  Member "second order region for gray wyner network":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "the dispersion of the gauss markov source")
  Member "first and second order coding theorems for mixed memoryless channels with general mixture":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "channel resolvability theorems for general sources and channels")
  Member "on the dispersions of three network information theory problems":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "gaussian multiple and random access in the finite blocklength regime")
  Member "second order resolvability intrinsic randomness and fixed length source coding for mixed sources information spectrum approach":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "interval algorithm for random number generation information spectrum approach")
  Member "second order slepian wolf coding theorems for non mixed and mixed sources":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "lossless source coding in the point to point multiple access and random access scenarios")
  Member "information spectrum approach to second order coding rate in channel coding":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "finite sample analysis of image registration")

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)