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: "universal communication over arbitrarily varying channels"
  Abstract: We consider the problem of universally communicating over an unknown and arbitrarily varying channel, using feedback. The focus of this paper is on determining the input behavior, and specifically, a prior distribution which is used to randomly generate the codebook. We pose the problem of setting the prior as a sequential universal prediction problem, that attempts to approach a given target rate, which depends on the unknown channel sequence. The main result is that, for a channel comprised of an unknown, arbitrary sequence of memoryless channels, there is a system using feedback and common randomness that asymptotically attains, with high probability, the capacity of the time-averaged channel, universally for every sequence of channels. While no prior knowledge of the channel sequence is assumed, the rate achieved meets or exceeds the traditional arbitrarily varying channel (AVC) capacity for every memoryless AVC defined over the same alphabets, and therefore the system universally attains the random code AVC capacity, without knowledge of the AVC parameters. The system we present combines rateless coding with a universal prediction scheme for the prior. We present rough upper bounds on the rates that can be achieved in this setting and lower bounds for the redundancies.

Connected through hyperedge HE-1 (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"
    - "list decoding random coding exponents and expurgated exponents"
    - "capacity results for arbitrarily varying wiretap channels"
    - "regret analysis of stochastic and nonstochastic multi armed bandit problems"

Connected through hyperedge HE-2 (induced by source paper "on optimal latency of communications"):
  with members:
    - "list decoding of polar codes"
    - "an adaptive successive cancellation list decoder for polar codes with cyclic redundancy check"
    - "communication over individual channels"

Connected through hyperedge HE-3 (induced by source paper "a universal decoder relative to a given family of metrics"):
  with members:
    - "universal decoding for gaussian intersymbol interference channels"
    - "universal decoding for arbitrary channels relative to a given class of decoding metrics"
    - "communication over individual channels a general framework"
    - "universal communication part i modulo additive channels"
    - "blind decoding of linear gaussian channels with isi capacity error exponent universality"

Connected through hyperedge HE-4 (induced by source paper "universal communication part ii channels with memory"):
  with members:
    - "the porosity of additive noise sequences"
    - "communication over individual channels"
    - "zero rate feedback can achieve the empirical capacity"
    - "universal communication part i modulo additive channels"

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)