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: "the physics of compressive sensing and the gradient based recovery algorithms"
  Abstract: The physics of compressive sensing (CS) and the gradient-based recovery algorithms are presented. First, the different forms for CS are summarized. Second, the physical meanings of coherence and measurement are given. Third, the gradient-based recovery algorithms and their geometry explanations are provided. Finally, we conclude the report and give some suggestion for future work.

Connected through hyperedge HE-1 (induced by source paper "simultaneous tensor completion and denoising by noise inequality constrained convex optimization"):
  with members:
    - "matrix completion with noise"
    - "exact matrix completion via convex optimization"

Connected through hyperedge HE-2 (induced by source paper "high quality image restoration from partial mixed adaptive random measurements"):
  with members:
    - "group based sparse representation for image restoration"
    - "stable image reconstruction using total variation minimization"
    - "fast and efficient compressive sensing using structurally random matrices"
    - "subspace pursuit for compressive sensing signal reconstruction"

Connected through hyperedge HE-3 (induced by source paper "smooth parafac decomposition for tensor completion"):
  with members:
    - "bayesian cp factorization of incomplete tensors with automatic rank determination"
    - "nuclear norm of higher order tensors"
    - "image processing using smooth ordering of its patches"
    - "compressed sensing and matrix completion with constant proportion of corruptions"

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)