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 "a randomized approach to the capacity of finite state channels"):
  Abstract: Inspired by the ideas from the field of stochastic approximation, we propose a randomized algorithm to compute the capacity of a finite-state channel with a Markovian input. When the mutual information rate of the channel is concave with respect to the chosen parameterization, we show that the proposed algorithm will almost surely converge to the capacity of the channel and derive the rate of convergence. We also discuss the convergence behavior of the algorithm without the concavity assumption.

Includes members:
  Member "the bethe permanent of a nonnegative matrix":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "gauges loops and polynomials for partition functions of graphical models")
  Member "non asymptotic equipartition properties for independent and identically distributed sources":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "new non asymptotic random channel coding theorems")
  Member "limit theorems in hidden markov models":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on continuous time gaussian channels")
  Member "entropy rate for hidden markov chains with rare transitions":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "novel lower bounds on the entropy rate of binary hidden markov processes")
  Member "entropy of hidden markov processes via cycle expansion":
    also connected through other hyperedges:
      (none)
  Member "asymptotics of entropy rate in special families of hidden markov chains":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "feedback capacity and coding for the bibo channel with a no repeated ones input constraint")
  Member "derivatives of entropy rate in special families of hidden markov chains":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "analyticity of entropy rates of continuous state hidden markov models")
  Member "taylor series expansions for the entropy rate of hidden markov processes":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "limit theorems in hidden markov models")

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)