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: "new ric bounds via l_q minimization with 0 q 1 in compressed sensing"
  Abstract: The restricted isometry constants (RICs) play an important role in exact recovery theory of sparse signals via l_q(0 =4/3 to guarantee the exact recovery of k sparse signals through the l_1 minimization. This paper aims to establish new RICs bounds via l_q(0 1, (ii)several sufficient conditions can be derived, such as for any 0 =2, for any 1/2 =1, (iii) the bound on \delta_k is given as well for any 0 =2) is even or \delta_k =3) is odd.

Connected through hyperedge HE-1 (induced by source paper "performance guarantees for schatten p quasi norm minimization in recovery of low rank matrices"):
  with members:
    - "sparse signal recovery by ell_q minimization under restricted isometry property"
    - "doa estimation in partially correlated noise using low rank sparse matrix decomposition"
    - "calibration using matrix completion with application to ultrasound tomography"
    - "matrix completion in colocated mimo radar recoverability bounds theoretical guarantees"
    - "on ric bounds of compressed sensing matrices for approximating sparse solutions using l q quasi norms"
    - "collaborative spectrum sensing from sparse observations in cognitive radio networks"
    - "matrix completion with noise"
    - "sparse recovery by non convex optimization instance optimality"

Connected through hyperedge HE-2 (induced by source paper "sparse signal recovery by ell_q minimization under restricted isometry property"):
  with members:
    - "sparse representation of a polytope and recovery of sparse signals and low rank matrices"
    - "sharp rip bound for sparse signal and low rank matrix recovery"

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)