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: "list decoding random coding exponents and expurgated exponents"
  Abstract: Some new results are derived concerning random coding error exponents and expurgated exponents for list decoding with a deterministic list size $L$. Two asymptotic regimes are considered, the fixed list-size regime, where $L$ is fixed independently of the block length $n$, and the exponential list-size, where $L$ grows exponentially with $n$. We first derive a general upper bound on the list-decoding average error probability, which is suitable for both regimes. This bound leads to more specific bounds in the two regimes. In the fixed list-size regime, the bound is related to known bounds and we establish its exponential tightness. In the exponential list-size regime, we establish the achievability of the well known sphere packing lower bound. Relations to guessing exponents are also provided. An immediate byproduct of our analysis in both regimes is the universality of the maximum mutual information (MMI) list decoder in the error exponent sense. Finally, we consider expurgated bounds at low rates, both using Gallager's approach and the Csisz\'ar-K\"orner-Marton approach, which is, in general better (at least for $L=1$). The latter expurgated bound, which involves the notion of {\it multi-information}, is also modified to apply to continuous alphabet channels, and in particular, to the Gaussian memoryless channel, where the expression of the expurgated bound becomes quite explicit.

Connected through hyperedge HE-1 (induced by source paper "mismatched guesswork"):
  with members:
    - "universal randomized guessing with application to asynchronous decentralized brute force attacks"
    - "why botnets work distributed brute force attacks need no synchronization"
    - "a characterization of guesswork on swiftly tilting curves"
    - "centralized vs decentralized multi agent guesswork"
    - "guesswork subject to a total entropy budget"
    - "multi user guesswork and brute force security"
    - "asymptotics and non asymptotics for universal fixed to variable source coding"
    - "erasure list random coding error exponents are not universally achievable"

Connected through hyperedge HE-2 (induced by source paper "learning an adversary s actions for secret communication"):
  with members:
    - "first and second order asymptotics in covert communication"
    - "generalizing multiple access wiretap and wiretap ii channel models achievable rates and cost of strong secrecy"
    - "a new wiretap channel model and its strong secrecy capacity"
    - "arbitrarily varying wiretap channels with type constrained states"
    - "semantic security capacity for wiretap channels of type ii"
    - "capacity results for arbitrarily varying wiretap channels"
    - "regret analysis of stochastic and nonstochastic multi armed bandit problems"
    - "universal communication over arbitrarily varying channels"

Connected through hyperedge HE-3 (induced by source paper "a characterization of guesswork on swiftly tilting curves"):
  with members:
    - "multi user guesswork and brute force security"
    - "asymptotics and non asymptotics for universal fixed to variable source coding"
    - "guesswork large deviations and shannon entropy"
    - "brute force searching the typical set and guesswork"
    - "guessing a password over a wireless channel on the effect of noise non uniformity"
    - "guessing revisited a large deviations approach"
    - "guessing under source uncertainty"

Connected through hyperedge HE-4 (induced by source paper "ratio list decoding"):
  with members:
    - "converse theorems for the dmc with mismatched decoding"
    - "expurgated random coding ensembles exponents refinements and connections"
    - "mismatched decoding error exponents second order rates and saddlepoint approximations"
    - "a general formula for the mismatch capacity"
    - "list decoding of polar codes"

Connected through hyperedge HE-5 (induced by source paper "generalized random gilbert varshamov codes"):
  with members:
    - "the generalized stochastic likelihood decoder random coding and expurgated bounds"
    - "expurgated random coding ensembles exponents refinements and connections"
    - "mismatched decoding error exponents second order rates and saddlepoint approximations"

Connected through hyperedge HE-6 (induced by source paper "arimoto r enyi conditional entropy and bayesian m ary hypothesis testing"):
  with members:
    - "guessing attacks on distributed storage systems"
    - "f divergence inequalities"
    - "on the listsize capacity with feedback"
    - "encoding tasks and renyi entropy"
    - "renyi divergence and kullback leibler divergence"
    - "moderate deviations analysis of binary hypothesis testing"
    - "on multiple hypothesis testing with rejection option"
    - "guessing under source uncertainty"

Connected through hyperedge HE-7 (induced by source paper "centralized vs decentralized multi agent guesswork"):
  with members:
    - "multi user guesswork and brute force security"
    - "asymptotics and non asymptotics for universal fixed to variable source coding"
    - "guesswork large deviations and shannon entropy"
    - "brute force searching the typical set and guesswork"
    - "guessing a password over a wireless channel on the effect of noise non uniformity"
    - "guessing under source uncertainty"

Connected through hyperedge HE-8 (induced by source paper "expurgated bounds for the asymmetric broadcast channel"):
  with members:
    - "exact random coding exponents and universal decoders for the asymmetric broadcast channel"
    - "the generalized stochastic likelihood decoder random coding and expurgated bounds"
    - "exact random coding error exponents of optimal bin index decoding"
    - "error exponents for broadcast channels with degraded message sets"

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)