human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "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.

Connected through hyperedge HE-1 (induced by source paper "information embedding on actions"):
  with members:
    - "successive refinement with decoder cooperation and its channel coding duals"
    - "on cascade source coding with a side information vending machine"
    - "on channels with action dependent states"
    - "cascade source coding with a side information vending machine"
    - "compression with actions"
    - "on real time coding with limited lookahead"
    - "multi terminal source coding with action dependent side information"
    - "coordination using implicit communication"

Connected through hyperedge HE-2 (induced by source paper "capacity and coding for the ising channel with feedback"):
  with members:
    - "feedback capacity of the compound channel"
    - "the capacity region of the degraded finite state broadcast channel"
    - "a coding theorem for a class of stationary channels with feedback"
    - "finite state channels with time invariant deterministic feedback"
    - "the capacity of channels with feedback"
    - "feedback capacity of the first order moving average gaussian channel"

Question: Please tell me which class the center node 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)