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: "relations between random coding exponents and the statistical physics of random codes"
  Abstract: The partition function pertaining to finite--temperature decoding of a (typical) randomly chosen code is known to have three types of behavior, corresponding to three phases in the plane of rate vs. temperature: the {\it ferromagnetic phase}, corresponding to correct decoding, the {\it paramagnetic phase}, of complete disorder, which is dominated by exponentially many incorrect codewords, and the {\it glassy phase} (or the condensed phase), where the system is frozen at minimum energy and dominated by subexponentially many incorrect codewords. We show that the statistical physics associated with the two latter phases are intimately related to random coding exponents. In particular, the exponent associated with the probability of correct decoding at rates above capacity is directly related to the free energy in the glassy phase, and the exponent associated with probability of error (the error exponent) at rates below capacity, is strongly related to the free energy in the paramagnetic phase. In fact, we derive alternative expressions of these exponents in terms of the corresponding free energies, and make an attempt to obtain some insights from these expressions. Finally, as a side result, we also compare the phase diagram associated with a simple finite-temperature universal decoder for discrete memoryless channels, to that of the finite--temperature decoder that is aware of the channel statistics.

Connected through hyperedge HE-1 (induced by source paper "on the reliability function of distributed hypothesis testing under optimal detection"):
  with members:
    - "on hypothesis testing against independence with multiple decision centers"
    - "on binary distributed hypothesis testing"
    - "distributed hypothesis testing over noisy channels"
    - "hypothesis testing over the two hop relay network"
    - "a large deviations approach to secure lossy compression"
    - "distributed binary detection with lossy data compression"
    - "neyman pearson test for zero rate multiterminal hypothesis testing"
    - "collaborative distributed hypothesis testing"

Connected through hyperedge HE-2 (induced by source paper "exact error and erasure exponents for the asymmetric broadcast channel"):
  with members:
    - "exact random coding exponents and universal decoders for the asymmetric broadcast channel"
    - "expurgated bounds for the asymmetric broadcast channel"
    - "random coding error exponents for the two user interference channel"
    - "simplified erasure list decoding"
    - "asymmetric evaluations of erasure and undetected error probabilities"
    - "exact random coding error exponents of optimal bin index decoding"
    - "erasure list random coding error exponents are not universally achievable"
    - "error exponents for broadcast channels with degraded message sets"

Connected through hyperedge HE-3 (induced by source paper "gaussian intersymbol interference channels with mismatch"):
  with members:
    - "on the asymptotic equivalence of circulant and toeplitz matrices"
    - "on the evaluation of the polyanskiy poor verdu converse bound for finite block length coding in awgn"
    - "random coding error exponents for the two user interference channel"
    - "universal decoding for gaussian intersymbol interference channels"
    - "erasure list exponents for slepian wolf decoding"
    - "mismatched decoding error exponents second order rates and saddlepoint approximations"
    - "a general formula for the mismatch capacity"
    - "analysis of mismatched estimation errors using gradients of partition functions"

Connected through hyperedge HE-4 (induced by source paper "the generalized stochastic likelihood decoder random coding and expurgated bounds"):
  with members:
    - "the likelihood encoder for lossy compression"
    - "universal decoding for source channel coding with side information"
    - "controllability of networked mimo systems"
    - "list decoding random coding exponents and expurgated exponents"
    - "exact random coding error exponents of optimal bin index decoding"
    - "a technique for deriving one shot achievability results in network information theory"
    - "erasure list exponents for slepian wolf decoding"

Connected through hyperedge HE-5 (induced by source paper "random coding error exponents for the two user interference channel"):
  with members:
    - "mismatched multi letter successive decoding for the multiple access channel"
    - "optimal achievable rates for interference networks with random codes"
    - "list decoding random coding exponents and expurgated exponents"
    - "exact correct decoding exponent of the wiretap channel decoder"
    - "exact random coding error exponents of optimal bin index decoding"
    - "erasure list random coding error exponents are not universally achievable"
    - "multiuser random coding techniques for mismatched decoding"
    - "the generalized random energy model and its application to the statistical physics of ensembles of hierarchical codes"

Connected through hyperedge HE-6 (induced by source paper "universal decoding for source channel coding with side information"):
  with members:
    - "exact random coding error exponents of optimal bin index decoding"
    - "erasure list exponents for slepian wolf decoding"
    - "universal decoding for arbitrary channels relative to a given class of decoding metrics"
    - "multiuser random coding techniques for mismatched decoding"
    - "communication over individual channels a general framework"
    - "the porosity of additive noise sequences"
    - "communication over individual channels"
    - "universal communication part i modulo additive channels"

Connected through hyperedge HE-7 (induced by source paper "on the reliability function of the discrete memoryless relay channel"):
  with members:
    - "multiuser coding techniques for mismatched decoding"
    - "multiuser random coding techniques for mismatched decoding"
    - "reliability in source coding with side information"
    - "moderate deviations of lossy source coding for discrete and gaussian sources"
    - "the gelfand pinsker channel strong converse and upper bound for the reliability function"
    - "information spectrum approach to second order coding rate in channel coding"
    - "capacity and random coding exponents for channel coding with side information"

Connected through hyperedge HE-8 (induced by source paper "statistical physics of random binning"):
  with members:
    - "exact random coding error exponents of optimal bin index decoding"
    - "optimum trade offs between the error exponent and the excess rate exponent of variable rate slepian wolf coding"
    - "erasure list exponents for slepian wolf decoding"
    - "improved source coding exponents via witsenhausen s rate"

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)