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 "signal classification under structured sparsity constraints"):
  Abstract: Object Classification is a key direction of research in signal and image processing, computer vision and artificial intelligence. The goal is to come up with algorithms that automatically analyze images and put them in predefined categories. This dissertation focuses on the theory and application of sparse signal processing and learning algorithms for image processing and computer vision, especially object classification problems. A key emphasis of this work is to formulate novel optimization problems for learning dictionary and structured sparse representations. Tractable solutions are proposed subsequently for the corresponding optimization problems. #R##N#An important goal of this dissertation is to demonstrate the wide applications of these algorithmic tools for real-world applications. To that end, we explored important problems in the areas of: #R##N#1. Medical imaging: histopathological images acquired from mammalian tissues, human breast tissues, and human brain tissues. #R##N#2. Low-frequency (UHF to L-band) ultra-wideband (UWB) synthetic aperture radar: detecting bombs and mines buried under rough surfaces. #R##N#3. General object classification: face, flowers, objects, dogs, indoor scenes, etc.

Includes members:
  Member "fast low rank shared dictionary learning for image classification":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "convolutional dictionary pair learning network for image representation learning")
  Member "learning a low rank shared dictionary for object classification":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "fast low rank shared dictionary learning for image classification")
  Member "adaptive matching pursuit for sparse signal recovery":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "fast low rank shared dictionary learning for image classification")
  Member "patch based convolutional neural network for whole slide tissue image classification":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "gastric histopathology image segmentation using a hierarchical conditional random field")
  Member "dfdl discriminative feature oriented dictionary learning for histopathological image classification":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "classification of histopathological breast cancer images using iterative vmd aided zernike moments textural signatures")

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.CV(Computer Vision and Pattern Recognition)