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 "universal wyner ziv coding for distortion constrained general side information"):
  Abstract: We investigate the Wyner-Ziv coding in which the statistics of the principal source is known but the statistics of the channel generating the side-information is unknown except that it is in a certain class. The class consists of channels such that the distortion between the principal source and the side-information is smaller than a threshold, but channels may be neither stationary nor ergodic. In this situation, we define a new rate-distortion function as the minimum rate such that there exists a Wyner-Ziv code that is universal for every channel in the class. Then, we show an upper bound and a lower bound on the rate-distortion function, and derive a matching condition such that the upper and lower bounds coincide. The relation between the new rate-distortion function and the rate-distortion function of the Heegard-Berger problem is also discussed.

Includes members:
  Member "channel coding and lossy source coding using a generator of constrained random numbers":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "communication for generating correlation a unifying survey")
  Member "tight exponential analysis of universally composable privacy amplification and its applications":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "communication for generating correlation a unifying survey")
  Member "achievability proof via output statistics of random binning":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "biometric and physical identifiers with correlated noise for controllable private authentication")
  Member "reliability in source coding with side information":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "on binary distributed hypothesis testing")
  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 "common reconstructions in the successive refinement problem with receiver side information")
  Member "universal source coding over generalized complementary delivery networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "the rate distortion function for product of two sources with side information at decoders")
  Member "efficient on line schemes for encoding individual sequences with side information at the decoder":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "data processing bounds for scalar lossy source codes with side information at the decoder")

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)