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 "the complexity of general valued csps"):
  Abstract: An instance of the Valued Constraint Satisfaction Problem (VCSP) is given by a finite set of variables, a finite domain of labels, and a sum of functions, each function depending on a subset of the variables. Each function can take finite values specifying costs of assignments of labels to its variables or the infinite value, which indicates infeasible assignments. The goal is to find an assignment of labels to the variables that minimizes the sum. #R##N#We study (assuming that P $\ne$ NP) how the complexity of this very general problem depends on the set of functions allowed in the instances, the so-called constraint language. The case when all allowed functions take values in $\{0,\infty\}$ corresponds to ordinary CSPs, where one deals only with the feasibility issue and there is no optimization. This case is the subject of the Algebraic CSP Dichotomy Conjecture predicting for which constraint languages CSPs are tractable and for which NP-hard. The case when all allowed functions take only finite values corresponds to finite-valued CSP, where the feasibility aspect is trivial and one deals only with the optimization issue. The complexity of finite-valued CSPs was fully classified by Thapper and \v{Z}ivn\'y. #R##N#An algebraic necessary condition for tractability of a general-valued CSP with a fixed constraint language was recently given by Kozik and Ochremiak. As our main result, we prove that if a constraint language satisfies this algebraic necessary condition, and the feasibility CSP corresponding to the VCSP with this language is tractable, then the VCSP is tractable. The algorithm is a simple combination of the assumed algorithm for the feasibility CSP and the standard LP relaxation. As a corollary, we obtain that a dichotomy for ordinary CSPs would imply a dichotomy for general-valued CSPs.

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 "combinatorial optimization algorithms via polymorphisms":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "and testing and robust judgement aggregation")
  Member "a galois connection for valued constraint languages of infinite size":
    also connected through other hyperedges:
      (none)
  Member "algebraic properties of valued constraint satisfaction problem":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "the complexity of boolean surjective general valued csps")
  Member "effectiveness of structural restrictions for hybrid csps":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "on planar valued csps")
  Member "local distribution and the symmetry gap approximability of multiway partitioning problems":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "optimizing item and subgroup configurations for social aware vr shopping")
  Member "sherali adams relaxations for valued csps":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "on planar valued csps")
  Member "robustly solvable constraint satisfaction problems":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "improved hardness for h colourings of g colourable graphs")

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)