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: "asymptotic estimates in information theory with non vanishing error probabilities"
  Abstract: This monograph presents a unified treatment of single- and multi-user problems in Shannon's information theory where we depart from the requirement that the error probability decays asymptotically in the blocklength. Instead, the error probabilities for various problems are bounded above by a non-vanishing constant and the spotlight is shone on achievable coding rates as functions of the growing blocklengths. This represents the study of asymptotic estimates with non-vanishing error probabilities. #R##N#In Part I, after reviewing the fundamentals of information theory, we discuss Strassen's seminal result for binary hypothesis testing where the type-I error probability is non-vanishing and the rate of decay of the type-II error probability with growing number of independent observations is characterized. In Part II, we use this basic hypothesis testing result to develop second- and sometimes, even third-order asymptotic expansions for point-to-point communication. Finally in Part III, we consider network information theory problems for which the second-order asymptotics are known. These problems include some classes of channels with random state, the multiple-encoder distributed lossless source coding (Slepian-Wolf) problem and special cases of the Gaussian interference and multiple-access channels. Finally, we discuss avenues for further research.

Connected through hyperedge HE-1 (induced by source paper "finite sample analysis of image registration"):
  with members:
    - "estimators for multivariate information measures in general probability spaces"
    - "end to end unsupervised deformable image registration with a convolutional neural network"
    - "a deep metric for multimodal registration"
    - "fundamental limits in multi image alignment"
    - "demystifying fixed k nearest neighbor information estimators"
    - "asymptotics and non asymptotics for universal fixed to variable source coding"
    - "channels with cost constraints strong converse and dispersion"
    - "a tight upper bound for the third order asymptotics for most discrete memoryless channels"

Connected through hyperedge HE-2 (induced by source paper "optimal resolution of change point detection with empirically observed statistics and erasures"):
  with members:
    - "distributed detection with empirically observed statistics"
    - "second order asymptotically optimal statistical classification"
    - "selective review of offline change point detection methods"
    - "time division is optimal for covert communication over some broadcast channels"
    - "fundamental limits of communication with low probability of detection"
    - "covert communication over noisy channels a resolvability perspective"
    - "asymptotically optimal matching of multiple sequences to source distributions and training sequences"
    - "moderate deviations in channel coding"

Connected through hyperedge HE-3 (induced by source paper "asymptotic expansions of smooth r e nyi entropies and their applications"):
  with members:
    - "variable length source dispersions differ under maximum and average error criteria"
    - "a unified framework for problems on guessing source coding and task partitioning"
    - "on the conditional smooth renyi entropy and its applications in guessing and source coding"
    - "on the smooth renyi entropy and variable length source coding allowing errors"
    - "encoding tasks and renyi entropy"
    - "variable length compression allowing errors"

Connected through hyperedge HE-4 (induced by source paper "second order asymptotics of sequential hypothesis testing"):
  with members:
    - "reliability of sequential hypothesis testing can be achieved by an almost fixed length test"
    - "refinement of the random coding bound"
    - "refinement of the sphere packing bound asymmetric channels"
    - "second order asymptotics in fixed length source coding and intrinsic randomness"

Connected through hyperedge HE-5 (induced by source paper "exponential strong converse for successive refinement with causal decoder side information"):
  with members:
    - "strong converse using change of measure arguments"
    - "exponential strong converse for content identification with lossy recovery"
    - "discrete lossy gray wyner revisited second order asymptotics large and moderate deviations"
    - "new strong converse for asymmetric broadcast channels"
    - "a proof of the strong converse theorem for gaussian multiple access channels"
    - "exponent function for one helper source coding problem at rates outside the rate region"
    - "strong successive refinability and rate distortion complexity tradeoff"
    - "on cooperative multiple access channels with delayed csi at transmitters"

Connected through hyperedge HE-6 (induced by source paper "resolution limits of noisy 20 questions estimation"):
  with members:
    - "unequal error protection querying policies for the noisy 20 questions problem"
    - "improved target acquisition rates with feedback codes"
    - "exponential strong converse for content identification with lossy recovery"
    - "smoothing brascamp lieb inequalities and strong converses for common randomness generation"
    - "the dispersion of nearest neighbor decoding for additive non gaussian channels"
    - "second order coding rates for channels with state"
    - "searching with measurement dependent noise"
    - "collaborative 20 questions for target localization"

Connected through hyperedge HE-7 (induced by source paper "covert communication over a compound channel"):
  with members:
    - "first and second order asymptotics in covert communication"
    - "covert communication over adversarially jammed channels"
    - "time division is optimal for covert communication over some broadcast channels"
    - "covert communication with channel state information at the transmitter"
    - "fundamental limits of communication with low probability of detection"
    - "covert communication over noisy channels a resolvability perspective"
    - "optimal throughput for covert communication over a classical quantum channel"
    - "limits of reliable communication with low probability of detection on awgn channels"

Connected through hyperedge HE-8 (induced by source paper "second and third order asymptotics of the continuous time poisson channel"):
  with members:
    - "the stochastic calculus approach to multi receiver poisson channels"
    - "fine asymptotics for universal one to one compression of parametric sources"
    - "asymptotics and non asymptotics for universal fixed to variable source coding"
    - "channels with cost constraints strong converse and dispersion"
    - "a tight upper bound for the third order asymptotics for most discrete memoryless channels"
    - "the log volume of optimal codes for memoryless channels asymptotically within a few nats"
    - "information spectrum approach to second order coding rate in channel coding"

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)