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: "the capacity of channels with feedback"
  Abstract: We introduce a general framework for treating channels with memory and feedback. First, we generalize Massey's concept of directed information and use it to characterize the feedback capacity of general channels. Second, we present coding results for Markov channels. This requires determining appropriate sufficient statistics at the encoder and decoder. Third, a dynamic programming framework for computing the capacity of Markov channels is presented. Fourth, it is shown that the average cost optimality equation (ACOE) can be viewed as an implicit single-letter characterization of the capacity. Fifth, scenarios with simple sufficient statistics are described.

Connected through hyperedge HE-1 (induced by source paper "a connection between feedback capacity and kalman filter for colored gaussian noises"):
  with members:
    - "generic variance bounds on estimation and prediction errors in time series analysis an entropy perspective"
    - "youla coding and computation of gaussian feedback capacity"
    - "feedback capacity of stationary gaussian channels further examined"
    - "sequential necessary and sufficient conditions for capacity achieving distributions of channels with memory and feedback"
    - "feedback capacity of gaussian channels revisited"
    - "information structures of capacity achieving distributions for feedback channels with memory and transmission cost stochastic optimal control variational equalities part i"
    - "capacity achieving feedback schemes for gaussian finite state markov channels with channel state information"
    - "convergence of fundamental limitations in feedback communication estimation and feedback control over gaussian channels"

Connected through hyperedge HE-2 (induced by source paper "computing the feedback capacity of finite state channels using reinforcement learning"):
  with members:
    - "deepcode feedback codes via deep learning"
    - "feedback capacity and coding for the bibo channel with a no repeated ones input constraint"
    - "a single letter upper bound on the feedback capacity of unifilar finite state channels"
    - "continuous control with deep reinforcement learning"
    - "capacity of a post channel with and without feedback"
    - "capacity and coding for the ising channel with feedback"
    - "finite state channels with time invariant deterministic feedback"

Connected through hyperedge HE-3 (induced by source paper "computable upper bounds on the capacity of finite state channels"):
  with members:
    - "capacity of burst noise erasure channels with and without feedback and input cost"
    - "feedback capacity and coding for the bibo channel with a no repeated ones input constraint"
    - "an upper bound for the capacity of amplitude constrained scalar awgn channel"
    - "dual capacity upper bounds for noisy runlength constrained channels"
    - "capacity bounds for discrete time amplitude constrained additive white gaussian noise channels"
    - "capacity of a post channel with and without feedback"
    - "capacity and coding for the ising channel with feedback"

Connected through hyperedge HE-4 (induced by source paper "graph based encoders and their performance for finite state channels with feedback"):
  with members:
    - "feedback capacity and coding for the 0 k rll input constrained bec"
    - "feedback capacity and coding for the bibo channel with a no repeated ones input constraint"
    - "a single letter upper bound on the feedback capacity of unifilar finite state channels"
    - "a comprehensive survey of recent advancements in molecular communication"
    - "capacity and coding for the ising channel with feedback"
    - "write channel model for bit patterned media recording"
    - "optimal feedback communication via posterior matching"

Connected through hyperedge HE-5 (induced by source paper "youla coding and computation of gaussian feedback capacity"):
  with members:
    - "control approach to computing the feedback capacity for stationary finite dimensional gaussian channels"
    - "upper bound on the capacity of gaussian channels with noisy feedback"
    - "bounds on the achievable rate of noisy feedback gaussian channels under linear feedback coding scheme"
    - "lqg control approach to gaussian broadcast channels with feedback"
    - "interpretations of directed information in portfolio theory data compression and hypothesis testing"
    - "optimal feedback communication via posterior matching"
    - "convergence of fundamental limitations in feedback communication estimation and feedback control over gaussian channels"
    - "on the feedback capacity of power constrained gaussian noise channels with memory"

Connected through hyperedge HE-6 (induced by source paper "transfer entropy in mdps with temporal logic specifications"):
  with members:
    - "a learning based optimal human robot collaboration with linear temporal logic constraints"
    - "optimal control in markov decision processes via distributed optimization"
    - "information nonanticipative rate distortion function and its applications"
    - "verification of markov decision processes using learning algorithms"
    - "optimal control of mdps with temporal logic constraints"

Connected through hyperedge HE-7 (induced by source paper "maximum likelihood upper bounds on the capacities of discrete information stable channels"):
  with members:
    - "capacity upper bounds for deletion type channels"
    - "a characterization of the number of subsequences obtained via the deletion channel"
    - "novel bounds on the capacity of the binary deletion channel"

Connected through hyperedge HE-8 (induced by source paper "feedback capacity and coding for the bibo channel with a no repeated ones input constraint"):
  with members:
    - "asymptotics of input constrained erasure channel capacity"
    - "dual capacity upper bounds for noisy runlength constrained channels"
    - "a single letter upper bound on the feedback capacity of unifilar finite state channels"
    - "an efficient feedback coding scheme with low error probability for discrete memoryless channels"
    - "a simple proof for the optimality of randomized posterior matching"
    - "can feedback increase the capacity of the energy harvesting channel"
    - "extrinsic jensen shannon divergence applications to variable length coding"
    - "capacity and coding for the ising channel with feedback"

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)