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 "large margin learning of compact binary image encodings"):
  Abstract: This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication.

Includes members:
  Member "learning hash functions using column generation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "deep multi index hashing for person re identification")
  Member "structboost boosting methods for predicting structured output variables":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "structured learning of binary codes with column generation")
  Member "positive semidefinite metric learning using boosting like algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "deep metric learning with bier boosting independent embeddings robustly")
  Member "local naive bayes nearest neighbor for image classification":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "towards universal representation for unseen action recognition")
  Member "incremental training of a detector using online sparse eigendecomposition":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a decomposition algorithm for sparse generalized eigenvalue problem")
  Member "self taught hashing for fast similarity search":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "learning compressed sentence representations for on device text processing")

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)