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 "on the reliability function of the discrete memoryless relay channel"):
  Abstract: Bounds on the reliability function for the discrete memoryless relay channel are derived using the method of types. Two achievable error exponents are derived based on partial decode-forward and compress-forward, which are well-known superposition block-Markov coding schemes. The derivations require combinations of the techniques involved in the proofs of Csiszar-Korner-Marton’s packing lemma for the error exponent of channel coding and Marton’s type covering lemma for the error exponent of source coding with a fidelity criterion. The decode-forward error exponent is evaluated on Sato’s relay channel. From this example, it is noted that to obtain the fastest possible decay in the error probability for a fixed effective coding rate, one ought to optimize the number of blocks in the block-Markov coding scheme assuming the blocklength within each block is large. An upper bound on the reliability function is also derived using ideas from Haroutunian’s lower bound on the error probability for point-to-point channel coding with feedback.

Includes members:
  Member "multiuser coding techniques for mismatched decoding":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "mismatched multi letter successive decoding for the multiple access channel")
  Member "multiuser random coding techniques for mismatched decoding":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "strategic communication with side information at the decoder")
  Member "reliability in source coding with side information":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on binary distributed hypothesis testing")
  Member "moderate deviations of lossy source coding for discrete and gaussian sources":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "exponential strong converse for content identification with lossy recovery")
  Member "the gelfand pinsker channel strong converse and upper bound for the reliability function":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "wiretap and gelfand pinsker channels analogy and its applications")
  Member "information spectrum approach to second order coding rate in channel coding":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "finite sample analysis of image registration")
  Member "relations between random coding exponents and the statistical physics of random codes":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "on the reliability function of distributed hypothesis testing under optimal detection")
  Member "capacity and random coding exponents for channel coding with side information":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "on the capacity of the carbon copy onto dirty paper channel")

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)