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: "verification based interval passing algorithm for compressed sensing"
  Abstract: We propose a verification-based Interval-Passing (IP) algorithm for iteratively reconstruction of nonnegative sparse signals using parity check matrices of low-density parity check (LDPC) codes as measurement matrices. The proposed algorithm can be considered as an improved IP algorithm by further incorporation of the mechanism of verification algorithm. It is proved that the proposed algorithm performs always better than either the IP algorithm or the verification algorithm. Simulation results are also given to demonstrate the superior performance of the proposed algorithm.

Connected through hyperedge HE-1 (induced by source paper "algebraic optimization of binary spatially coupled measurement matrices for interval passing"):
  with members:
    - "failure analysis of the interval passing algorithm for compressed sensing"
    - "a generalized algebraic approach to optimizing sc ldpc codes"
    - "on failing sets of the interval passing algorithm for compressed sensing"
    - "on the minimum distance of array based spatially coupled low density parity check codes"
    - "a simple message passing algorithm for compressed sensing"
    - "the effect of spatial coupling on compressive sensing"
    - "optimally tuned iterative reconstruction algorithms for compressed sensing"
    - "message passing algorithms for compressed sensing i motivation and construction"

Connected through hyperedge HE-2 (induced by source paper "failure analysis of the interval passing algorithm for compressed sensing"):
  with members:
    - "asymptotic analysis and spatial coupling of counter braids"
    - "on the minimum stopping distance of array low density parity check codes"
    - "information theoretically optimal compressed sensing via spatial coupling and approximate message passing"
    - "a simple message passing algorithm for compressed sensing"
    - "message passing algorithms for compressed sensing"
    - "on the stopping distance and the stopping redundancy of codes"

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)