human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "variable length source dispersions differ under maximum and average error criteria"):
  Abstract: Variable-length compression without prefix-free constraints and with side-information available at both encoder and decoder is considered. Instead of requiring the code to be error-free, we allow for it to have a non-vanishing error probability. We derive one-shot bounds on the optimal average codeword length by proposing two new information quantities; namely, the conditional and unconditional $\varepsilon$-cutoff entropies. Using these one-shot bounds, we obtain the second-order asymptotics of the problem under two different formalisms---the average and maximum probabilities of error over the realization of the side-information. While the first-order terms in the asymptotic expansions for both formalisms are identical, we find that the source dispersion under the average error formalism is, in most cases, strictly smaller than its maximum counterpart. Applications to a certain class of guessing problems, previously studied by Kuzuoka (2019), are also discussed.

Includes members:
  Member "on the conditional smooth renyi entropy and its applications in guessing and source coding":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "asymptotic expansions of smooth r e nyi entropies and their applications")
  Member "asymptotics and non asymptotics for universal fixed to variable source coding":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "finite sample analysis of image registration")
  Member "an information spectrum approach to weak variable length source coding with side information":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "variable length resolvability for general sources and channels")
  Member "variable length compression allowing errors":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "asymptotic expansions of smooth r e nyi entropies and their applications")
  Member "information spectrum approach to second order coding rate in channel coding":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "finite sample analysis of image registration")
  Member "duality between channel capacity and rate distortion with two sided state information":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "communication over an arbitrarily varying channel under a state myopic encoder")
  Member "second order asymptotics in fixed length source coding and intrinsic randomness":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "finite sample analysis of image registration")

Question: Please tell me which class the source paper 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)