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: "l1 projections with box constraints"
  Abstract: Similarities between simplex projection with upper bounds and L1 projection are explored. Criteria for a-priori determination of sequence in which various constraints become active are derived, and this sequence is used to develop efficient algorithms for projecting a vector onto the L1-ball while observing box constraints. Three projection methods are presented. The first projection method performs exact projection in O(n2) worst case complexity, where n is the space dimension. Using a novel criteria for ordering constraints, the second projection method has a worst case complexity of O(n log n). The third projection method is a worst case linear time algorithm having O(n) complexity. The upper bounds defined for the projected entries guide the L1-ball projection to more meaningful predictions.

Connected through hyperedge HE-1 (induced by source paper "predict and constrain modeling cardinality in deep structured prediction"):
  with members:
    - "learning to learn by gradient descent by gradient descent"
    - "unrolled generative adversarial networks"
    - "end to end sequence labeling via bi directional lstm cnns crf"
    - "highway and residual networks learn unrolled iterative estimation"
    - "structured prediction energy networks"
    - "visual recognition by counting instances a multi instance cardinality potential kernel"
    - "fully connected deep structured networks"
    - "learning deep structured models"

Connected through hyperedge HE-2 (induced by source paper "reconstructing point sets from distance distributions"):
  with members:
    - "solving complex quadratic systems with full rank random matrices"
    - "phase retrieval via wirtinger flow theory and algorithms"
    - "string reconstruction from substring compositions"

Connected through hyperedge HE-3 (induced by source paper "decomposition methods for large scale lp decoding"):
  with members:
    - "hierarchical and high girth qc ldpc codes"
    - "counting in graph covers a combinatorial characterization of the bethe entropy function"
    - "online alternating direction method"
    - "error floor approximation for ldpc codes in the awgn channel"
    - "improved linear programming decoding of ldpc codes and bounds on the minimum and fractional distance"
    - "efficient implementation of linear programming decoding"
    - "probabilistic analysis of linear programming decoding"
    - "interior point algorithms for linear programming decoding"

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.DS(Data Structures and Algorithms)