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 real time coding with limited lookahead"
  Abstract: A real time coding system with lookahead consists of a memoryless source, a memoryless channel, an encoder, which encodes the source symbols sequentially with knowledge of future source symbols upto a fixed finite lookahead, d, with or without feedback of the past channel output symbols and a decoder, which sequentially constructs the source symbols using the channel output. The objective is to minimize the expected per-symbol distortion. For a fixed finite lookahead d>=1 we invoke the theory of controlled markov chains to obtain an average cost optimality equation (ACOE), the solution of which, denoted by D(d), is the minimum expected per-symbol distortion. With increasing d, D(d) bridges the gap between causal encoding, d=0, where symbol by symbol encoding-decoding is optimal and the infinite lookahead case, d=\infty, where Shannon Theoretic arguments show that separation is optimal. We extend the analysis to a system with finite state decoders, with or without noise-free feedback. For a Bernoulli source and binary symmetric channel, under hamming loss, we compute the optimal distortion for various source and channel parameters, and thus obtain computable bounds on D(d). We also identify regions of source and channel parameters where symbol by symbol encoding-decoding is suboptimal. Finally, we demonstrate the wide applicability of our approach by applying it in additional coding scenarios, such as the case where the sequential decoder can take cost constrained actions affecting the quality or availability of side information about the source.

Connected through hyperedge HE-1 (induced by source paper "information embedding on actions"):
  with members:
    - "successive refinement with decoder cooperation and its channel coding duals"
    - "on cascade source coding with a side information vending machine"
    - "on channels with action dependent states"
    - "cascade source coding with a side information vending machine"
    - "compression with actions"
    - "multi terminal source coding with action dependent side information"
    - "coordination using implicit communication"
    - "distributed and cascade lossy source coding with a side information vending machine"

Connected through hyperedge HE-2 (induced by source paper "distributed and cascade lossy source coding with a side information vending machine"):
  with members:
    - "multi terminal source coding with action dependent side information"
    - "robust coding for lossy computing with receiver side observation costs"
    - "source coding with a side information vending machine"
    - "alphabet sizes of auxiliary random variables in canonical inner bounds"
    - "on the role of mmse estimation in approaching the information theoretic limits of linear gaussian channels shannon meets wiener"

Connected through hyperedge HE-3 (induced by source paper "structure theorems for real time variable rate coding with and without side information"):
  with members:
    - "information theoretic viewpoints on optimal causal coding decoding problems"
    - "on the wyner ziv problem for individual sequences"

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)