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 "extracting wyner s common randomness using polar codes"):
  Abstract: Explicit construction of polar codes for the Gray-Wyner network is studied. We show that Wyner's common information plays an essential role in constructing polar codes for both lossless and lossy Gray-Wyner coding problems. For discrete joint sources, extracting Wyner's common randomness can be viewed as a lossy compression problem, which is accomplished by extending polar coding for a single source to a pair of joint sources with doubled alphabet size. We show that the lossless Gray-Wyner region can be achieved by an upgraded or degraded version of the common randomness. For joint Gaussian sources, we prove that extracting Wyner's common randomness is equivalent to lossy compression for a single Gaussian source, meaning that Wyner's common randomness can be extracted by utilizing polar lattice for quantization and represented by a lattice Gaussian random variable.

Includes members:
  Member "polar lattices are good for lossy compression":
    also connected through other hyperedges:
      (none)
  Member "polar lattices for lossy compression":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "polar codes and polar lattices for the heegard berger problem")
  Member "the lossy common information of correlated sources":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "characterization of conditional independence and weak realizations of multivariate gaussian random variables applications to networks")
  Member "achieving awgn channel capacity with lattice gaussian coding":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "well rounded lattices towards optimal coset codes for gaussian and fading wiretap channels")
  Member "how to construct polar codes":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "polar codes and their quantum domain counterparts")
  Member "channel polarization a method for constructing capacity achieving codes for symmetric binary input memoryless channels":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "reed muller codes theory and algorithms")

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)