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: "optimization of zero delay mappings for distributed coding by deterministic annealing"
  Abstract: This paper studies the optimization of zero-delay analog mappings in a network setting that involves distributed coding. The cost surface is known to be non-convex, and known greedy methods tend to get trapped in poor locally optimal solutions that depend heavily on initialization. We derive an optimization algorithm based on the principles of "deterministic annealing", a powerful global optimization framework that has been successfully employed in several disciplines, including, in our recent work, to a simple zero-delay analog communications problem. We demonstrate strict superiority over the descent based methods, as well as present example mappings whose properties lend insights on the workings of the solution and relations with digital distributed coding.

Connected through hyperedge HE-1 (induced by source paper "zero delay joint source channel coding in the presence of interference known at the encoder"):
  with members:
    - "on zero delay source channel coding"
    - "on conditions for linearity of optimal estimation"
    - "joint source channel codes for mimo block fading channels"

Connected through hyperedge HE-2 (induced by source paper "deterministic annealing based optimization for zero delay source channel coding in networks"):
  with members:
    - "on zero delay source channel coding"
    - "a deterministic annealing approach to optimization of zero delay source channel codes"
    - "robust analog function computation via wireless multiple access channels"
    - "distributed scalar quantization for computing high resolution analysis and extensions"
    - "rate region of the quadratic gaussian two encoder source coding problem"

Connected through hyperedge HE-3 (induced by source paper "on zero delay source channel coding"):
  with members:
    - "a deterministic annealing approach to witsenhausen s counterexample"
    - "a deterministic annealing approach to optimization of zero delay source channel codes"
    - "reduced dimension linear transform coding of correlated signals in networks"
    - "data processing bounds for scalar lossy source codes with side information at the decoder"
    - "on conditions for linearity of optimal estimation"

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)