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: "on the conditional smooth renyi entropy and its applications in guessing and source coding"
  Abstract: A novel definition of the conditional smooth Renyi entropy, which is different from that of Renner and Wolf, is introduced. It is shown that our definition of the conditional smooth Renyi entropy is appropriate to give lower and upper bounds on the optimal guessing moment in a guessing problem where the guesser is allowed to stop guessing and declare an error. Further a general formula for the optimal guessing exponent is given. In particular, a single-letterized formula for mixture of i.i.d. sources is obtained. Another application in the problem of source coding with the common side-information available at the encoder and decoder is also demonstrated.

Connected through hyperedge HE-1 (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"
    - "asymptotic estimates in information theory with non vanishing error probabilities"
    - "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-2 (induced by source paper "variable length source dispersions differ under maximum and average error criteria"):
  with members:
    - "asymptotics and non asymptotics for universal fixed to variable source coding"
    - "an information spectrum approach to weak variable length source coding with side information"
    - "variable length compression allowing errors"
    - "information spectrum approach to second order coding rate in channel coding"
    - "duality between channel capacity and rate distortion with two sided state information"
    - "second order asymptotics in fixed length source coding and intrinsic randomness"

Connected through hyperedge HE-3 (induced by source paper "tight bounds on the r enyi entropy via majorization with applications to guessing and compression"):
  with members:
    - "maximum entropy interval aggregations"
    - "distributed task encoding"
    - "reducing guesswork via an unreliable oracle"
    - "guessing attacks on distributed storage systems"
    - "bounds on the entropy of a function of a random variable and their applications"
    - "on the renyi divergence joint range of relative entropies and a channel coding theorem"
    - "on the smooth renyi entropy and variable length source coding allowing errors"
    - "encoding tasks and renyi entropy"

Connected through hyperedge HE-4 (induced by source paper "non asymptotic fundamental limits of guessing subject to distortion"):
  with members:
    - "cumulant generating function of codeword lengths in variable length lossy compression allowing positive excess distortion probability"

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)