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 "quadratic decomposable submodular function minimization"):
  Abstract: We introduce a new convex optimization problem, termed quadratic decomposable submodular function minimization. The problem is closely related to decomposable submodular function minimization and arises in many learning on graphs and hypergraphs settings, such as graph-based semi-supervised learning and PageRank. We approach the problem via a new dual strategy and describe an objective that may be optimized via random coordinate descent (RCD) methods and projections onto cones. We also establish the linear convergence rate of the RCD algorithm and develop efficient projection algorithms with provable performance guarantees. Numerical experiments in semi-supervised learning on hypergraphs confirm the efficiency of the proposed algorithm and demonstrate the significant improvements in prediction accuracy with respect to state-of-the-art methods.

Includes members:
  Member "revisiting decomposable submodular function minimization with incidence relations":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "localized flow based clustering in hypergraphs")
  Member "inhomogoenous hypergraph clustering with applications":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "hypergraph motifs concepts algorithms and discoveries")
  Member "cheeger inequalities for submodular transformations":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "quadratic decomposable submodular function minimization theory and practice")
  Member "diffusion operator and spectral analysis for directed hypergraph laplacian":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "quadratic decomposable submodular function minimization theory and practice")
  Member "random coordinate descent methods for minimizing decomposable submodular functions":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "parallel batch dynamic graphs algorithms and lower bounds")
  Member "provable submodular minimization using wolfe s algorithm":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "quadratic decomposable submodular function minimization theory and practice")
  Member "reflection methods for user friendly submodular optimization":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "quadratic decomposable submodular function minimization theory and practice")
  Member "learning by transduction":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "relational neural machines")

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.LG(Machine Learning)