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: "a simple proof for the optimality of randomized posterior matching"
  Abstract: Posterior matching (PM) is a sequential horizon-free feedback communication scheme introduced by the authors, who also provided a rather involved optimality proof showing it achieves capacity for a large class of memoryless channels. Naghshvar et al considered a non-sequential variation of PM with a fixed number of messages and a random decision-time, and gave a simpler proof establishing its optimality via a novel Shannon-Jensen divergence argument. Another simpler optimality proof was given by Li and El Gamal, who considered a fixed-rate fixed block-length variation of PM with an additional randomization. Both these works also provided error exponent bounds. However, their simpler achievability proofs apply only to discrete memoryless channels, and are restricted to a non-sequential setup with a fixed number of messages. In this paper, we provide a short and transparent proof for the optimality of the fully sequential horizon-free PM scheme over general memoryless channels. Borrowing the key randomization idea of Li and El Gamal, our proof is based on analyzing the random walk behavior of the shrinking posterior intervals induced by a reversed iterated function system (RIFS) decoder.

Connected through hyperedge HE-1 (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"
    - "the impact of beamwidth on temporal channel variation in vehicular channels and its implications"

Connected through hyperedge HE-2 (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"
    - "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"
    - "information theoretic viewpoints on optimal causal coding decoding problems"

Connected through hyperedge HE-3 (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"
    - "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"
    - "optimal feedback communication via posterior matching"

Connected through hyperedge HE-4 (induced by source paper "feedback capacity and coding for the 0 k rll input constrained bec"):
  with members:
    - "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"
    - "an efficient feedback coding scheme with low error probability for discrete memoryless channels"
    - "extrinsic jensen shannon divergence applications to variable length coding"
    - "modulation coding for flash memories"
    - "capacity and coding for the ising channel with feedback"
    - "optimal feedback communication via posterior matching"
    - "the capacity of channels with feedback"

Connected through hyperedge HE-5 (induced by source paper "searching with measurement dependent noise"):
  with members:
    - "extrinsic jensen shannon divergence applications to variable length coding"
    - "collaborative 20 questions for target localization"
    - "boolean compressed sensing and noisy group testing"
    - "communication over individual channels"
    - "interference mitigation in large random wireless networks"
    - "zero rate feedback can achieve the empirical capacity"
    - "optimal feedback communication via posterior matching"

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)