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 reduction from valued csp to min cost homomorphism problem for digraphs"
  Abstract: In a valued constraint satisfaction problem (VCSP), the goal is to find an assignment of labels to variables that minimizes a given sum of functions. Each function in the sum depends on a subset of variables, takes values which are rational numbers or infinity, and is chosen from a fixed finite set of functions called a constraint language. The case when all functions take only values 0 and infinity is known as the constraint satisfaction problem (CSP). It is known that any CSP with fixed constraint language is polynomial-time equivalent to one where the constraint language contains a single binary relation (i.e. a digraph). A recent proof of this by Bulin et al. gives such a reduction that preserves most of the algebraic properties of the constraint language that are known to characterize the complexity of the corresponding CSP. We adapt this proof to the more general setting of VCSP to show that each VCSP with a fixed finite (valued) constraint language is equivalent to one where the constraint language consists of one $\{0,\infty\}$-valued binary function (i.e. a digraph) and one finite-valued unary function, the latter problem known as the (extended) Minimum Cost Homomorphism Problem for digraphs. We also show that our reduction preserves some important algebraic properties of the (valued) constraint language.

Connected through hyperedge HE-1 (induced by source paper "binarisation for valued constraint satisfaction problems"):
  with members:
    - "the power of sherali adams relaxations for general valued csps"
    - "a galois connection for weighted relational clones of infinite size"
    - "a finer reduction of constraint problems to digraphs"
    - "algebraic properties of valued constraint satisfaction problem"
    - "the complexity of general valued csps"
    - "sherali adams relaxations for valued csps"
    - "robustly solvable constraint satisfaction problems"
    - "an algebraic theory of complexity for discrete optimization"

Connected through hyperedge HE-2 (induced by source paper "the power of sherali adams relaxations for general valued csps"):
  with members:
    - "binarisation for valued constraint satisfaction problems"
    - "algebraic properties of valued constraint satisfaction problem"
    - "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"

Connected through hyperedge HE-3 (induced by source paper "necessary conditions for tractability of valued csps"):
  with members:
    - "algebraic properties of valued constraint satisfaction problem"
    - "the complexity of general valued csps"
    - "the power of linear programming for general valued csps"
    - "computational complexity of the minimum cost homomorphism problem on three element domains"
    - "an effective fusion technique of cloud computing and networking series"
    - "the power of linear programming for valued csps a constructive characterization"
    - "extensions of the minimum cost homomorphism problem"

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.CC(Computational Complexity)