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 "a unified framework for one shot achievability via the poisson matching lemma"):
  Abstract: We introduce a fundamental lemma called the Poisson matching lemma, and apply it to prove one-shot achievability results for various settings, namely channels with state information at the encoder, lossy source coding with side information at the decoder, joint source-channel coding, broadcast channels, distributed lossy source coding, multiple access channels, channel resolvability and wiretap channels. Our one-shot bounds improve upon the best known one-shot bounds in most of the aforementioned settings (except multiple access channels, channel resolvability and wiretap channels, where we recover bounds comparable to the best known bounds), with shorter proofs in some settings even when compared to the conventional asymptotic approach using typicality. The Poisson matching lemma replaces both the packing and covering lemmas, greatly simplifying the error analysis. This paper extends the work of Li and El Gamal on Poisson functional representation, which mainly considered variable-length source coding settings, whereas this paper studies fixed-length settings, and is not limited to source coding, showing that the Poisson functional representation is a viable alternative to typicality for most problems in network information theory.

Includes members:
  Member "minimax learning for remote prediction":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "vector gaussian ceo problem under logarithmic loss and applications")
  Member "strong functional representation lemma and applications to coding theorems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "communication for generating correlation a unifying survey")
  Member "the likelihood encoder for lossy compression":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "keyless covert communication via channel state information")
  Member "one shot mutual covering lemma and marton s inner bound with a common message":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "sharp bounds for mutual covering")
  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 "on the dispersions of the gel fand pinsker channel and dirty paper coding":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "sharp bounds for mutual covering")
  Member "non asymptotic output statistics of random binning and its applications":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "physical layer security in the finite blocklength regime over fading channels")
  Member "distributed channel synthesis":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "gaussian approximation of quantization error for estimation from compressed data")

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)