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: "tomographic image reconstruction using dictionary priors"
  Abstract: We describe and examine a framework for tomographic image reconstruction where prior knowledge about the solution is available in the form of training images. We first construct a dictionary that contains prototype elements from these images. Then by using the dictionary as a prior to regularize the inverse problem, and looking for a solution with a sparse representation in the dictionary, we formulate the reconstruction problem in a convex optimization framework. Our computational experiments clarify the choice and interplay of the model parameters and the regularization parameters, and they show that in few-projection settings we are able to produce better images with more structural features than the total variation approach.

Connected through hyperedge HE-1 (induced by source paper "a tensor based dictionary learning approach to tomographic image reconstruction"):
  with members:
    - "novel methods for multilinear data completion and de noising based on tensor svd"
    - "an alternating direction algorithm for matrix completion with nonnegative factors"
    - "non negative matrix factorization with sparseness constraints"

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.CV(Computer Vision and Pattern Recognition)