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: "a deterministic annealing approach to optimization of zero delay source channel codes"
  Abstract: This paper studies optimization of zero-delay source-channel codes, and specifically the problem of obtaining globally optimal transformations that map between the source space and the channel space, under a given transmission power constraint and for the mean square error distortion. Particularly, we focus on the setting where the decoder has access to side information, whose cost surface is known to be riddled with local minima. Prior work derived the necessary conditions for optimality of the encoder and decoder mappings, along with a greedy optimization algorithm that imposes these conditions iteratively, in conjunction with the heuristic "noisy channel relaxation" method to mitigate poor local minima. While noisy channel relaxation is arguably effective in simple settings, it fails to provide accurate global optimization results in more complicated settings including the decoder with side information as considered in this paper. We propose a global optimization algorithm based on the ideas of "deterministic annealing"- a non-convex optimization method, derived from information theoretic principles with analogies to statistical physics, and successfully employed in several problems including clustering, vector quantization and regression. We present comparative numerical results that show strict superiority of the proposed algorithm over greedy optimization methods as well as over the noisy channel relaxation.

Connected through hyperedge HE-1 (induced by source paper "zero delay source channel coding with a one bit adc front end and correlated side information at the receiver"):
  with members:
    - "joint source channel coding with one bit adc front end"
    - "one bit massive mimo channel estimation and high order modulations"
    - "massive mimo with 1 bit adc"
    - "on zero delay source channel coding"
    - "at low snr asymmetric quantizers are better"

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"
    - "optimization of zero delay mappings for distributed coding by deterministic annealing"
    - "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 "analog multiple descriptions a zero delay source channel coding approach"):
  with members:
    - "deterministic annealing based optimization for zero delay source channel coding in networks"
    - "a deterministic annealing approach to witsenhausen s counterexample"
    - "on zero delay source channel coding"

Connected through hyperedge HE-4 (induced by source paper "on zero delay source channel coding"):
  with members:
    - "a deterministic annealing approach to witsenhausen s counterexample"
    - "optimization of zero delay mappings for distributed coding by deterministic annealing"
    - "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"

Connected through hyperedge HE-5 (induced by source paper "a deterministic annealing approach to witsenhausen s counterexample"):
  with members:
    - "a deterministic annealing optimization approach for witsenhausen s and related decentralized control settings"

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)