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: "on the separation of lossy source network coding and channel coding in wireline networks"
  Abstract: This paper proves the separation between source-network coding and channel coding in networks of noisy, discrete, memoryless channels. We show that the set of achievable distortion matrices in delivering a family of dependent sources across such a network equals the set of achievable distortion matrices for delivering the same sources across a distinct network which is built by replacing each channel by a noiseless, point-to-point bit-pipe of the corresponding capacity. Thus a code that applies source-network coding across links that are made almost lossless through the application of independent channel coding across each link asymptotically achieves the optimal performance across the network as a whole.

Connected through hyperedge HE-1 (induced by source paper "constrained source coding with side information"):
  with members:
    - "interactive function computation with reconstruction constraints"
    - "heegard berger and cascade source coding problems with common reconstruction constraints"
    - "separation of source network coding and channel coding in wireline networks"
    - "duality between channel capacity and rate distortion with two sided state information"

Connected through hyperedge HE-2 (induced by source paper "hybrid coding an interface for joint source channel coding and network communication"):
  with members:
    - "wireless network information flow a deterministic approach"
    - "communication to within a fidelity criterion over unknown networks by reduction to reliable communication problems over unknown networks"
    - "optimality and approximate optimality of source channel separation in networks"
    - "the achievable distortion region of bivariate gaussian source on gaussian broadcast channel"
    - "correlated sources over broadcast channels"
    - "wyner ziv coding over broadcast channels digital schemes"
    - "outer bounds on the admissible source region for broadcast channels with dependent sources"
    - "comments on broadcast channels with arbitrarily correlated sources"

Connected through hyperedge HE-3 (induced by source paper "reduced dimension linear transform coding of correlated signals in networks"):
  with members:
    - "a rank metric approach to error control in random network coding"
    - "coding for errors and erasures in random network coding"
    - "a direct formulation for sparse pca using semidefinite programming"

Connected through hyperedge HE-4 (induced by source paper "on capacity region of wiretap networks"):
  with members:
    - "network equivalence in the presence of an eavesdropper"
    - "network coding capacity regions via entropy functions"
    - "separation of source network coding and channel coding in wireline networks"

Connected through hyperedge HE-5 (induced by source paper "separation of source network coding and channel coding in wireline networks"):
  with members:
    - "optimality and approximate optimality of source channel separation in networks"
    - "a theory of network equivalence parts i and ii"

Connected through hyperedge HE-6 (induced by source paper "optimality and approximate optimality of source channel separation in networks"):
  with members:
    - "separation of source network coding and channel coding in wireline networks"
    - "cascade and triangular source coding with side information at the first two nodes"
    - "cascade multiterminal source coding"
    - "hybrid coding for gaussian broadcast channels with gaussian sources"
    - "approximate characterizations for the gaussian source broadcast distortion region"
    - "multicasting correlated multi source to multi sink over a network"
    - "on multistage successive refinement for wyner ziv source coding with degraded side informations"
    - "coding into a source a direct inverse rate distortion theorem"

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)