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: "the likelihood encoder for source coding"
  Abstract: The likelihood encoder with a random codebook is demonstrated as an effective tool for source coding. Coupled with a soft covering lemma (associated with channel resolvability), likelihood encoders yield simple achievability proofs for known results, such as rate-distortion theory. They also produce a tractable analysis for secure rate-distortion theory and strong coordination.

Connected through hyperedge HE-1 (induced by source paper "the likelihood encoder for lossy compression"):
  with members:
    - "joint source channel secrecy using hybrid coding"
    - "a rate distortion based secrecy system with side information at the decoders"
    - "a generalized typicality for abstract alphabets"
    - "the likelihood encoder for lossy source compression"
    - "a technique for deriving one shot achievability results in network information theory"
    - "non asymptotic output statistics of random binning and its applications"
    - "a connection between good rate distortion codes and backward dmcs"
    - "distributed channel synthesis"

Connected through hyperedge HE-2 (induced by source paper "lossy compression with near uniform encoder outputs"):
  with members:
    - "strong coordination over multi hop line networks"
    - "second order asymptotics in fixed length source coding and intrinsic randomness"

Connected through hyperedge HE-3 (induced by source paper "e_ gamma resolvability"):
  with members:
    - "f divergence inequalities"
    - "the likelihood encoder for lossy compression"
    - "soft covering with high probability"
    - "bounds among f divergences"
    - "semantic security capacity for wiretap channels of type ii"
    - "one shot mutual covering lemma and marton s inner bound with a common message"
    - "resolvability in e γ with applications to lossy compression and wiretap channels"
    - "robustness of sparse recovery via f minimization a topological viewpoint"

Connected through hyperedge HE-4 (induced by source paper "joint source channel secrecy using hybrid coding"):
  with members:
    - "rate distortion based physical layer secrecy with applications to multimode fiber"
    - "a rate distortion based secrecy system with side information at the decoders"
    - "the likelihood encoder for lossy source compression"
    - "distributed channel synthesis"
    - "rate distortion theory for secrecy systems"
    - "hybrid coding an interface for joint source channel coding and network communication"
    - "source channel secrecy with causal disclosure"
    - "secrecy is cheap if the adversary must reconstruct"

Connected through hyperedge HE-5 (induced by source paper "secure coordination with a two sided helper"):
  with members:
    - "optimal equivocation in secrecy systems a special case of distortion based characterization"
    - "on secure source coding with side information at the encoder"
    - "distributed channel synthesis"
    - "rate distortion theory for secrecy systems"
    - "using a secret key to foil an eavesdropper"
    - "multiterminal source coding under logarithmic loss"
    - "secure lossy source coding with side information at the decoders"
    - "a framework for partial secrecy"

Connected through hyperedge HE-6 (induced by source paper "a rate distortion based secrecy system with side information at the decoders"):
  with members:
    - "secure transmission of sources over noisy channels with side information at the receivers"
    - "the likelihood encoder for lossy source compression"
    - "a bit of secrecy for gaussian source compression"
    - "distributed channel synthesis"
    - "rate distortion theory for secrecy systems"
    - "secrecy is cheap if the adversary must reconstruct"
    - "using a secret key to foil an eavesdropper"
    - "secure lossy source coding with side information at the decoders"

Connected through hyperedge HE-7 (induced by source paper "secrecy in cascade networks"):
  with members:
    - "secure cascade channel synthesis"
    - "optimal equivocation in secrecy systems a special case of distortion based characterization"
    - "distributed channel synthesis"
    - "rate distortion theory for secrecy systems"
    - "secrecy is cheap if the adversary must reconstruct"
    - "multiterminal source coding under logarithmic loss"
    - "multiterminal source coding with an entropy based distortion measure"

Connected through hyperedge HE-8 (induced by source paper "the henchman problem measuring secrecy by the minimum distortion in a list"):
  with members:
    - "the likelihood encoder for lossy compression"
    - "the likelihood encoder for lossy source compression"
    - "distributed channel synthesis"
    - "rate distortion theory for secrecy systems"
    - "on the shannon cipher system with a wiretapper guessing subject to distortion and reliability requirements"

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)