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: "optimal feedback communication via posterior matching"
  Abstract: In this paper we introduce a fundamental principle for optimal communication over general memoryless channels in the presence of noiseless feedback, termed posterior matching. Using this principle, we devise a (simple, sequential) generic feedback transmission scheme suitable for a large class of memoryless channels and input distributions, achieving any rate below the corresponding mutual information. This provides a unified framework for optimal feedback communication in which the Horstein scheme (BSC) and the Schalkwijk-Kailath scheme (AWGN channel) are special cases. Thus, as a corollary, we prove that the Horstein scheme indeed attains the BSC capacity, settling a longstanding conjecture. We further provide closed form expressions for the error probability of the scheme over a range of rates, and derive the achievable rates in a mismatch setting where the scheme is designed according to the wrong channel model. Several illustrative examples of the posterior matching scheme for specific channels are given, and the corresponding error probability expressions are evaluated. The proof techniques employed utilize novel relations between information rates and contraction properties of iterated function systems.

Connected through hyperedge HE-1 (induced by source paper "feedback channel communication with low precision arithmetic"):
  with members:
    - "deepcode feedback codes via deep learning"
    - "interactive schemes for the awgn channel with noisy feedback"
    - "variations on a theme by schalkwijk and kailath"
    - "concatenated coding for the awgn channel with noisy feedback"

Connected through hyperedge HE-2 (induced by source paper "low complexity algorithms for transmission of short blocks over the bsc with full feedback"):
  with members:
    - "finite blocklength performance of sequential transmission over bsc with noiseless feedback"
    - "variable length convolutional coding for short blocklengths with decision feedback"
    - "extrinsic jensen shannon divergence applications to variable length coding"

Connected through hyperedge HE-3 (induced by source paper "active learning and csi acquisition for mmwave initial alignment"):
  with members:
    - "improved target acquisition rates with feedback codes"
    - "linear block coding for efficient beam discovery in millimeter wave communication networks"
    - "overview of millimeter wave communications for fifth generation 5g wireless networks with a focus on propagation models"
    - "comparative analysis of initial access techniques in 5g mmwave cellular networks"
    - "hybrid beamforming for massive mimo a survey"
    - "active learning from imperfect labelers"
    - "an efficient feedback coding scheme with low error probability for discrete memoryless channels"
    - "a simple proof for the optimality of randomized posterior matching"

Connected through hyperedge HE-4 (induced by source paper "construction and analysis of posterior matching in arbitrary dimensions via optimal transport"):
  with members:
    - "variable length codes for channels with memory and feedback error exponent lower bounds"
    - "an efficient feedback coding scheme with low error probability for discrete memoryless channels"
    - "a simple proof for the optimality of randomized posterior matching"
    - "extrinsic jensen shannon divergence applications to variable length coding"
    - "searching with measurement dependent noise"
    - "collaborative 20 questions for target localization"
    - "bit wise unequal error protection for variable length block codes with feedback"
    - "active sequential hypothesis testing"

Connected through hyperedge HE-5 (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"
    - "the capacity of channels with feedback"

Connected through hyperedge HE-6 (induced by source paper "joint source channel coding for the transmission of correlated sources over two way channels"):
  with members:
    - "lossy transmission of correlated sources over two way channels"
    - "adaptation is useless for two discrete additive noise two way channels"
    - "two way networks when adaptation is useless"

Connected through hyperedge HE-7 (induced by source paper "finite blocklength performance of sequential transmission over bsc with noiseless feedback"):
  with members:
    - "variable length convolutional coding for short blocklengths with decision feedback"
    - "extrinsic jensen shannon divergence applications to variable length coding"

Connected through hyperedge HE-8 (induced by source paper "stabilizing a linear system using phone calls when time is information"):
  with members:
    - "optimal causal rate constrained sampling of the wiener process"
    - "theory and implementation of event triggered stabilization over digital channels"
    - "stabilizing a linear system using phone calls"
    - "tracking and control of gauss markov processes over packet drop channels with acknowledgments"
    - "event triggered stabilization of linear systems under bounded bit rates"
    - "inscribed matter communication part ii"
    - "information theory of molecular communication directions and challenges"
    - "almost practical tree codes"

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)