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: "finite state channels with time invariant deterministic feedback"
  Abstract: We consider capacity of discrete-time channels with feedback for the general case where the feedback is a time-invariant deterministic function of the output samples. Under the assumption that the channel states take values in a finite alphabet, we find an achievable rate and an upper bound on the capacity. We further show that when the channel is indecomposable, and has no intersymbol interference (ISI), its capacity is given by the limit of the maximum of the (normalized) directed information between the input $X^N$ and the output $Y^N$, i.e. $C = \lim_{N \to \infty} \frac{1}{N} \max I(X^N \to Y^N)$, where the maximization is taken over the causal conditioning probability $Q(x^N||z^{N-1})$ defined in this paper. The capacity result is used to show that the source-channel separation theorem holds for time-invariant determinist feedback. We also show that if the state of the channel is known both at the encoder and the decoder then feedback does not increase capacity.

Connected through hyperedge HE-1 (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"
    - "the capacity of channels with feedback"

Connected through hyperedge HE-2 (induced by source paper "bidirectional information flow and the roles of privacy masks in cloud based control"):
  with members:
    - "utility privacy tradeoffs in databases an information theoretic approach"
    - "differentially private iterative synchronous consensus"

Connected through hyperedge HE-3 (induced by source paper "time invariant feedback strategies do not increase capacity of agn channels driven by stable and certain unstable autoregressive noise"):
  with members:
    - "information structures of capacity achieving distributions for feedback channels with memory and transmission cost stochastic optimal control variational equalities part i"
    - "feedback capacity of stationary gaussian channels"

Connected through hyperedge HE-4 (induced by source paper "capacity of two way channels with symmetry properties"):
  with members:
    - "a survey on non orthogonal multiple access for 5g networks research challenges and future trends"
    - "two way interference channel capacity how to have the cake and eat it too"
    - "adaptation is useless for two discrete additive noise two way channels"
    - "three way channels with multiple unicast sessions capacity approximation via network transformation"
    - "a survey on device to device communication in cellular networks"
    - "capacity results for two classes of three way channels"
    - "two way networks when adaptation is useless"
    - "a coding theorem for a class of stationary channels with feedback"

Connected through hyperedge HE-5 (induced by source paper "cheeger inequalities for submodular transformations"):
  with members:
    - "finding cheeger cuts in hypergraphs via heat equation"
    - "polynomial time algorithms for submodular laplacian systems"
    - "submodular hypergraphs p laplacians cheeger inequalities and spectral clustering"
    - "inhomogoenous hypergraph clustering with applications"
    - "spectral properties of hypergraph laplacian and approximation algorithms"
    - "improved cheeger s inequality and analysis of local graph partitioning using vertex expansion and expansion profile"
    - "heat kernel based community detection"
    - "provable submodular minimization using wolfe s algorithm"

Connected through hyperedge HE-6 (induced by source paper "capacity of burst noise erasure channels with and without feedback and input cost"):
  with members:
    - "feedback capacity and coding for the bibo channel with a no repeated ones input constraint"
    - "asymptotics of input constrained erasure channel capacity"
    - "feedback does not increase the capacity of compound channels with additive noise"
    - "can feedback increase the capacity of the energy harvesting channel"
    - "zero delay sequential transmission of markov sources over burst erasure channels"
    - "windowed decoding of protograph based ldpc convolutional codes over erasure channels"
    - "capacity and coding for the ising channel with feedback"
    - "a coding theorem for a class of stationary channels with feedback"

Connected through hyperedge HE-7 (induced by source paper "a unified bellman equation for causal information and value in markov decision processes"):
  with members:
    - "empowerment an introduction"

Connected through hyperedge HE-8 (induced by source paper "sequential necessary and sufficient conditions for capacity achieving distributions of channels with memory and feedback"):
  with members:
    - "capacity achieving distributions information lossless randomized strategies for feedback channels with memory the lqg theory of directed information part ii"
    - "a single letter upper bound on the feedback capacity of unifilar finite state channels"
    - "information structures of capacity achieving distributions for feedback channels with memory and transmission cost stochastic optimal control variational equalities part i"
    - "capacity of binary state symmetric channel with and without feedback and transmission cost"
    - "information structures for feedback capacity of channels with memory and transmission cost stochastic optimal control variational equalities part i"
    - "capacity of a post channel with and without feedback"
    - "directed information on abstract spaces properties and variational equalities"
    - "directed information on abstract spaces properties and extremum problems"

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)