human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "an algorithmic refinement of maxent induces a thermodynamic like behaviour in the reprogrammability of generative mechanisms"):
  Abstract: Reprogramming a generative mechanism to produce a different object is associated with a cost. Here we use the notion of algorithmic randomness to quantify such a cost when reprogramming networks. We identify an asymmetry in a measure of reprogrammability, suggesting an analogy with a thermodynamic asymmetry. The principle of maximum entropy (Maxent) quantifies the evolution of entropy or the uncertainty during state transitions in systems confined to an equilibrium condition. Here we define a generalisation based on algorithmic randomness not restricted to equilibrium physics, based on both distance to algorithmic randomness and reprogrammability. We advance a constructive preferential attachment algorithm approximating a maximally algorithmic random network. Hence, as a refinement on classical Maxent, networks can be quantified with respect to their distance to a maximally algorithmic random network. Our analysis suggests that the reprogrammability asymmetry originates from its non-monotonic relationship to algorithmic randomness. Our analysis motivates further work on the degree of algorithmic asymmetries in systems depending on their reprogrammability capabilities.

Includes members:
  Member "parameter free network sparsification and data reduction by minimal algorithmic information loss":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "ab initio algorithmic causal deconvolution of intertwined programs and networks by generative mechanism")
  Member "coding theorem like behaviour and emergence of the universal distribution from resource bounded algorithmic probability":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "algorithmic probability guided supervised machine learning on non differentiable spaces")
  Member "low algorithmic complexity entropy deceiving graphs":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "the thermodynamics of network coding and an algorithmic refinement of the principle of maximum entropy")
  Member "algorithmic data analytics small data matters and correlation versus causation":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "parameter free network sparsification and data reduction by minimal algorithmic information loss")
  Member "a decomposition method for global evaluation of shannon entropy and local estimations of algorithmic complexity":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "algorithmic probability guided supervised machine learning on non differentiable spaces")
  Member "shannon information and kolmogorov complexity":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "intelligence physics and information the tradeoff between accuracy and simplicity in machine learning")

Question: Please tell me which class the source paper 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)