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: "a dsatur based algorithm for the equitable coloring problem"
  Abstract: This paper describes a new exact algorithm for the Equitable Coloring Problem, a coloring problem where the sizes of two arbitrary color classes differ in at most one unit. Based on the well known DSatur algorithm for the classic Coloring Problem, a pruning criterion arising from equity constraints is proposed and analyzed. The good performance of the algorithm is shown through computational experiments over random and benchmark instances.

Connected through hyperedge HE-1 (induced by source paper "gradient descent based weight learning for grouping problems application on graph coloring and equitable graph coloring"):
  with members:
    - "an overview of gradient descent optimization algorithms"
    - "adam a method for stochastic optimization"
    - "variations on memetic algorithms for graph coloring problems"
    - "a tabu search heuristic for the equitable coloring problem"
    - "recent advances in graph partitioning"
    - "deep generative stochastic networks trainable by backprop"
    - "estimating or propagating gradients through stochastic neurons for conditional computation"
    - "breaking instance independent symmetries in exact graph coloring"

Connected through hyperedge HE-2 (induced by source paper "spectrum graph coloring and applications to wi fi channel assignment"):
  with members:
    - "dichotomies properties on computational complexity of s packing coloring problems"

Connected through hyperedge HE-3 (induced by source paper "a tabu search heuristic for the equitable coloring problem"):
  with members:
    - "a polyhedral approach for the equitable coloring problem"
    - "small approximate pareto sets for bi objective shortest paths and other problems"

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.DM(Discrete Mathematics)