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 "to feed or not to feed back"):
  Abstract: We establish results assessing the fundamental limits on reliable communication over Finite State Channels (FSCs), when the encoder and the decoder can control the availability or the quality of the feedback. The instantaneous feedback is a function of a cost constrained action taken by the encoder, a cost constrained action taken by the decoder, and the channel output. Achievability is through construction of a sequence of convergent achievable rates, using a simple scheme based on ‘code tree’ generation, that generates channel input symbols along with encoder and decoder actions. For a given block length N, we give an upper bound on the maximum achievable rate. For stationary indecomposable channels without intersymbol interference (ISI), the capacity is given as the limit of normalized directed information between the input and output sequence, maximized over an appropriate set of causally conditioned distributions. As important special cases, we characterize (a) the framework of ‘to feed or not to feed back’ where either the encoder or the decoder takes binary actions to determine whether current channel output will be fed back to the encoder, with a constraint on the fraction of channel outputs that are fed back, (b) the capacity of ‘coding on the backward link’ in FSCs, i.e., when the decoder sends limited-rate instantaneous coded noise-free feedback on the backward link.

Includes members:
  Member "interpretations of directed information in portfolio theory data compression and hypothesis testing":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "capacity of continuous channels with memory via directed information neural estimator")
  Member "zero error feedback capacity via dynamic programming":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "on real time coding with limited lookahead")
  Member "feedback capacity of the compound channel":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on the reliability function of the common message broadcast channel with variable length feedback")
  Member "finite state channels with time invariant deterministic feedback":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "computing the feedback capacity of finite state channels using reinforcement learning")
  Member "feedback capacity of stationary gaussian channels":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "capacity of continuous channels with memory via directed information neural estimator")
  Member "the capacity of channels with feedback":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a connection between feedback capacity and kalman filter for colored gaussian noises")

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)