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: "binarisation for valued constraint satisfaction problems"
  Abstract: We study methods for transforming valued constraint satisfaction problems (VCSPs) to binary VCSPs. First, we show that the standard dual encoding preserves many aspects  of the algebraic properties that capture the computational complexity of VCSPs. Second, we extend the reduction of CSPs to binary CSPs described by BulA©n et al. [Log. Methods Comput. Sci., 11 (2015)] to VCSPs. This reduction establishes that VCSPs over a fixed valued constraint language are polynomial-time equivalent to minimum-cost homomorphism problems over a fixed digraph.

Connected through hyperedge HE-1 (induced by source paper "toward a dichotomy for approximation of h coloring"):
  with members:
    - "interval like graphs and digraphs"
    - "towards a characterization of constant factor approximable finite valued csps"
    - "bi arc digraphs and conservative polymorphisms"
    - "the complexity of general valued csps"
    - "local distribution and the symmetry gap approximability of multiway partitioning problems"
    - "conservative constraint satisfaction re revisited"
    - "computational complexity of the minimum cost homomorphism problem on three element domains"
    - "the dichotomy of list homomorphisms for digraphs"

Connected through hyperedge HE-2 (induced by source paper "the power of sherali adams relaxations for general valued csps"):
  with members:
    - "algebraic properties of valued constraint satisfaction problem"
    - "a reduction from valued csp to min cost homomorphism problem for digraphs"
    - "the complexity of general valued csps"
    - "local distribution and the symmetry gap approximability of multiway partitioning problems"
    - "robustly solvable constraint satisfaction problems"
    - "sum of squares proofs and the quest toward optimal algorithms"
    - "half integrality lp branching and fpt algorithms"
    - "approximate constraint satisfaction requires large lp relaxations"

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)