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 "error exponents of erasure list decoding revisited via moments of distance enumerators"):
  Abstract: The analysis of random coding error exponents pertaining to erasure/list decoding, due to Forney, is revisited. Instead of using Jensen's inequality as well as some other inequalities in the derivation, we demonstrate that an exponentially tight analysis can be carried out by assessing the relevant moments of certain distance enumerators. The resulting bound has the following advantages: (i) it is at least as tight as Forney's bound, (ii) under certain symmetry conditions associated with the channel and the random coding distribution, it is simpler than Forney's bound in the sense that it involves an optimization over one parameter only (rather than two), and (iii) in certain special cases, like the binary symmetric channel (BSC), the optimum value of this parameter can be found in closed form, and so, there is no need to conduct a numerical search. We have not found yet a numerical example where this new bound is strictly better than Forney's bound and this may provide an additional evidence to support Forney's conjecture that his bound is tight for the average code. However, when applying the proposed analysis technique to a certain universal decoder with erasures, we demonstrate that it may yield significantly tighter exponential error bounds. We believe that this technique can be useful in simplifying and improving exponential error bounds in other problem settings as well.

Includes members:
  Member "error exponents of optimum decoding for the interference channel":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "exact error and erasure exponents for the asymmetric broadcast channel")
  Member "on the error exponents of arq channels with deadlines":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "errors and erasures decoding for block codes with feedback")
  Member "relations between random coding exponents and the statistical physics of random codes":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on the reliability function of distributed hypothesis testing under optimal detection")

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)