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: "universal source coding over generalized complementary delivery networks"
  Abstract: This paper deals with a universal coding problem for a certain kind of multiterminal source coding network called a generalized complementary delivery network. In this network, messages from multiple correlated sources are jointly encoded, and each decoder has access to some of the messages to enable it to reproduce the other messages. Both fixed-to-fixed length and fixed-to-variable length lossless coding schemes are considered. Explicit constructions of universal codes and the bounds of the error probabilities are clarified by using methods of types and graph-theoretical analysis.

Connected through hyperedge HE-1 (induced by source paper "universal wyner ziv coding for distortion constrained general side information"):
  with members:
    - "channel coding and lossy source coding using a generator of constrained random numbers"
    - "tight exponential analysis of universally composable privacy amplification and its applications"
    - "achievability proof via output statistics of random binning"
    - "reliability in source coding with side information"
    - "rate distortion with side information at many decoders"
    - "the rate distortion function for product of two sources with side information at decoders"
    - "efficient on line schemes for encoding individual sequences with side information at the decoder"
    - "hash property and coding theorems for sparse matrices and maximum likelihood coding"

Connected through hyperedge HE-2 (induced by source paper "the rate distortion function for product of two sources with side information at decoders"):
  with members:
    - "source coding problems with conditionally less noisy side information"
    - "rate distortion with side information at many decoders"
    - "lecture notes on network information theory"
    - "side information scalable source coding"
    - "on multistage successive refinement for wyner ziv source coding with degraded side informations"

Connected through hyperedge HE-3 (induced by source paper "universal coding for lossless and lossy complementary delivery problems"):
  with members:
    - "multiterminal source coding with complementary delivery"
    - "universal coding for correlated sources with complementary delivery"
    - "on the wyner ziv problem for individual sequences"

Connected through hyperedge HE-4 (induced by source paper "multiterminal source coding with complementary delivery"):
  with members:
    - "universal coding for correlated sources with complementary delivery"

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)