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 "the likelihood encoder for lossy compression"):
  Abstract: A likelihood encoder is studied in the context of lossy source compression. The analysis of the likelihood encoder is based on the soft-covering lemma. It is demonstrated that the use of a likelihood encoder together with the soft-covering lemma yields simple achievability proofs for classical source coding problems. The cases of the point-to-point rate-distortion function, the rate-distortion function with side information at the decoder (i.e., the Wyner-Ziv problem), and the multi-terminal source coding inner bound (i.e., the Berger-Tung problem) are examined in this paper. Furthermore, a non-asymptotic analysis is used for the point-to-point case to examine the upper bound on the excess distortion provided by this method. The likelihood encoder is also related to a recent alternative technique using the properties of random binning.

Includes members:
  Member "joint source channel secrecy using hybrid coding":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "source channel secrecy for shannon cipher system")
  Member "a rate distortion based secrecy system with side information at the decoders":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "keyless covert communication via channel state information")
  Member "a generalized typicality for abstract alphabets":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "the renyi capacity and center")
  Member "the likelihood encoder for lossy source compression":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "secure cascade channel synthesis")
  Member "a technique for deriving one shot achievability results in network information theory":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "exponential strong converse for successive refinement with causal decoder side information")
  Member "non asymptotic output statistics of random binning and its applications":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "physical layer security in the finite blocklength regime over fading channels")
  Member "a connection between good rate distortion codes and backward dmcs":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "the rate distortion risk in estimation from compressed data")
  Member "the likelihood encoder for source coding":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "lossy compression with near uniform encoder outputs")

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)