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 "a galois connection for weighted relational clones of infinite size"):
  Abstract: A Galois connection between clones and relational clones on a fixed finite domain is one of the cornerstones of the so-called algebraic approach to the computational complexity of non-uniform Constraint Satisfaction Problems (CSPs). Cohen et al. established a Galois connection between finitely-generated weighted clones and finitely-generated weighted relational clones [SICOMP’13], and asked whether this connection holds in general. We answer this question in the affirmative for weighted (relational) clones with real weights and show that the complexity of the corresponding valued CSPs is preserved.

Includes members:
  Member "the power of sherali adams relaxations for general valued csps":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "new dependencies of hierarchies in polynomial optimization")
  Member "the complexity of finite valued csps":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "the complexity of boolean surjective general valued csps")
  Member "necessary conditions for tractability of valued csps":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "representing fitness landscapes by valued constraints to understand the complexity of local search")
  Member "algebraic properties of valued constraint satisfaction problem":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "the complexity of boolean surjective general valued csps")
  Member "the complexity of general valued csps":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "the complexity of boolean surjective general valued csps")
  Member "sherali adams relaxations for valued csps":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "on planar valued csps")
  Member "an algebraic theory of complexity for discrete optimization":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "the complexity of boolean surjective general valued csps")
  Member "the complexity of conservative valued csps":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "representing fitness landscapes by valued constraints to understand the complexity of local search")

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.CC(Computational Complexity)