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 "common reconstructions in the successive refinement problem with receiver side information"):
  Abstract: We study a variant of the successive refinement problem with receiver side information where the receivers require identical reconstructions. We present general inner and outer bounds for the rate region for this variant and present a single-letter characterization of the admissible rate region for several classes of the joint distribution of the source and the side information. The characterization indicates that the side information can be fully used to reduce the communication rates via binning; however, the reconstruction functions can depend only on the G\'acs-K\"orner common randomness shared by the two receivers. Unlike existing (inner and outer) bounds to the rate region of the general successive refinement problem, the characterization of the admissible rate region derived for several settings of the variant studied requires only one auxiliary random variable. Using the derived characterization, we establish that the admissible rate region is not continuous in the underlying source source distribution even though the problem formulation does not involve zero-error or functional reconstruction constraints.

Includes members:
  Member "vector gaussian rate distortion with variable side information":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "vector gaussian successive refinement with degraded side information")
  Member "rate distortion function for a heegard berger problem with two sources and degraded reconstruction sets":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "on the information bottleneck problems models connections applications and information theoretic views")
  Member "heegard berger and cascade source coding problems with common reconstruction constraints":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "hypothesis testing over the two hop relay network")
  Member "source coding problems with conditionally less noisy side information":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "biometric and physical identifiers with correlated noise for controllable private authentication")
  Member "rate distortion with side information at many decoders":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "distributed hypothesis testing with concurrent detections")
  Member "the rate distortion function for product of two sources with side information at decoders":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "lp bounds for rate distortion with variable side information")
  Member "side information scalable source coding":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "extended gray wyner system with complementary causal side information")
  Member "on multistage successive refinement for wyner ziv source coding with degraded side informations":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "vector gaussian successive refinement with degraded side information")

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)