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: "towards a stable definition of kolmogorov chaitin complexity"
  Abstract: Laboratoire d’Informatique Fondamentale de Lille (CNRS)Institut d’Histoire et de Philosophie des Sciences et des Techniques, (CNRS, ENS, Universite Paris 1)´Carnegie Mellon Universityhector.zenil@liﬂ.fr, hector.zenil-chavez@malix.univ-paris1.fr, hectorz@andrew.cmu.eduAbstract. Although information content is invariant up to an additive constant, the range of pos-sible additive constants applicable to programming languages is so large that in practice it plays amajor role in the actual evaluation of K(s), the Kolmogorov-Chaitin complexity of a string s. Someattempts have been made to arrive at a framework stable enough for a concrete deﬁnition of K, in-dependent of any constant under a programming language, by appealing to the naturalness of thelanguage in question. The aim of this paper is to present an approach to overcome the problem bylooking at a set of models of computation converging in output probability distribution such that thatnaturalness can be inferred, thereby providing a framework for a stable deﬁnition of Kunder the setof convergent models of computation.Keywords: algorithmic information theory, program-size complexity.

Connected through hyperedge HE-1 (induced by source paper "coding theorem like behaviour and emergence of the universal distribution from resource bounded algorithmic probability"):
  with members:
    - "computing by nowhere increasing complexity"
    - "algorithmically probable mutations reproduce aspects of evolution such as convergence rate genetic memory and modularity"
    - "natural scene statistics mediate the perception of image complexity"
    - "correlation of automorphism group size and topological properties with program size complexity evaluations of graphs and complex networks"
    - "calculating kolmogorov complexity from the output frequency distributions of small turing machines"
    - "kolmogorov complexity and solovay functions"
    - "optimal ordered problem solver"

Connected through hyperedge HE-2 (induced by source paper "a computable measure of algorithmic probability by finite approximations"):
  with members:
    - "algorithmic data analytics small data matters and correlation versus causation"
    - "a decomposition method for global evaluation of shannon entropy and local estimations of algorithmic complexity"
    - "algorithmic complexity for short binary strings applied to psychology a primer"
    - "algorithmic complexity for psychology a user friendly implementation of the coding theorem method"
    - "natural scene statistics mediate the perception of image complexity"
    - "correlation of automorphism group size and topological properties with program size complexity evaluations of graphs and complex networks"
    - "correspondence and independence of numerical evaluations of algorithmic information measures"
    - "calculating kolmogorov complexity from the output frequency distributions of small turing machines"

Connected through hyperedge HE-3 (induced by source paper "algorithmic complexity for short binary strings applied to psychology a primer"):
  with members:
    - "calculating kolmogorov complexity from the output frequency distributions of small turing machines"
    - "numerical evaluation of algorithmic complexity for short strings a glance into the innermost structure of randomness"

Connected through hyperedge HE-4 (induced by source paper "correspondence and independence of numerical evaluations of algorithmic information measures"):
  with members:
    - "two dimensional kolmogorov complexity and validation of the coding theorem method by compressibility"
    - "on the kolmogorov chaitin complexity for short sequences"
    - "most programs stop quickly or never halt"

Connected through hyperedge HE-5 (induced by source paper "calculating kolmogorov complexity from the output frequency distributions of small turing machines"):
  with members:
    - "algorithmic complexity for short binary strings applied to psychology a primer"
    - "correlation of automorphism group size and topological properties with program size complexity evaluations of graphs and complex networks"
    - "correspondence and independence of numerical evaluations of algorithmic information measures"
    - "two dimensional kolmogorov complexity and validation of the coding theorem method by compressibility"
    - "numerical evaluation of algorithmic complexity for short strings a glance into the innermost structure of randomness"
    - "image characterization and classification by physical complexity"
    - "compression based investigation of the dynamical properties of cellular automata and other systems"
    - "on the algorithmic nature of the world"

Connected through hyperedge HE-6 (induced by source paper "two dimensional kolmogorov complexity and validation of the coding theorem method by compressibility"):
  with members:
    - "correspondence and independence of numerical evaluations of algorithmic information measures"
    - "calculating kolmogorov complexity from the output frequency distributions of small turing machines"
    - "compression based investigation of the dynamical properties of cellular automata and other systems"
    - "on the kolmogorov chaitin complexity for short sequences"
    - "most programs stop quickly or never halt"

Connected through hyperedge HE-7 (induced by source paper "an algorithmic approach to information and meaning"):
  with members:
    - "numerical evaluation of algorithmic complexity for short strings a glance into the innermost structure of randomness"
    - "image characterization and classification by physical complexity"
    - "on the algorithmic nature of the world"
    - "on the kolmogorov chaitin complexity for short sequences"
    - "most programs stop quickly or never halt"
    - "shannon information and kolmogorov complexity"
    - "the similarity metric"

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)