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: "improved parameterized algorithms for constraint satisfaction"
  Abstract: For many constraint satisfaction problems, the algorithm which chooses a random assignment achieves the best possible approximation ratio. For instance, a simple random assignment for {\sc Max-E3-Sat} allows 7/8-approximation and for every $\eps >0$ there is no polynomial-time ($7/8+\eps$)-approximation unless P=NP. Another example is the {\sc Permutation CSP} of bounded arity. Given the expected fraction $\rho$ of the constraints satisfied by a random assignment (i.e. permutation), there is no $(\rho+\eps)$-approximation algorithm for every $\eps >0$, assuming the Unique Games Conjecture (UGC). #R##N#In this work, we consider the following parameterization of constraint satisfaction problems. Given a set of $m$ constraints of constant arity, can we satisfy at least $\rho m +k$ constraint, where $\rho$ is the expected fraction of constraints satisfied by a random assignment? {\sc Constraint Satisfaction Problems above Average} have been posed in different forms in the literature \cite{Niedermeier2006,MahajanRamanSikdar09}. We present a faster parameterized algorithm for deciding whether $m/2+k/2$ equations can be simultaneously satisfied over ${\mathbb F}_2$. As a consequence, we obtain $O(k)$-variable bikernels for {\sc boolean CSPs} of arity $c$ for every fixed $c$, and for {\sc permutation CSPs} of arity 3. This implies linear bikernels for many problems under the "above average" parameterization, such as {\sc Max-$c$-Sat}, {\sc Set-Splitting}, {\sc Betweenness} and {\sc Max Acyclic Subgraph}. As a result, all the parameterized problems we consider in this paper admit $2^{O(k)}$-time algorithms. #R##N#We also obtain non-trivial hybrid algorithms for every Max $c$-CSP: for every instance $I$, we can either approximate $I$ beyond the random assignment threshold in polynomial time, or we can find an optimal solution to $I$ in subexponential time.

Connected through hyperedge HE-1 (induced by source paper "constraint satisfaction problems parameterized above or below tight bounds a survey"):
  with members:
    - "simultaneously satisfying linear equations over mathbb f _2 maxlin2 and max r lin2 parameterized above average"
    - "hypercontractive inequality for pseudo boolean functions of bounded fourier width"
    - "a new bound for 3 satisfiable maxsat and its algorithmic application"
    - "parameterized complexity of maxsat above average"
    - "on multiway cut parameterized above lower bounds"
    - "a new lower bound on the maximum number of satisfied clauses in max sat and its algorithmic application"
    - "betweenness parameterized above tight lower bound"
    - "a probabilistic approach to problems parameterized above or below tight bounds"

Connected through hyperedge HE-2 (induced by source paper "simultaneously satisfying linear equations over mathbb f _2 maxlin2 and max r lin2 parameterized above average"):
  with members:
    - "hitting forbidden minors approximation and kernelization"
    - "all ternary permutation constraint satisfaction problems parameterized above average have kernels with quadratic numbers of variables"
    - "cross composition a new technique for kernelization lower bounds"
    - "a probabilistic approach to problems parameterized above or below tight bounds"
    - "note on max lin 2 above average"

Connected through hyperedge HE-3 (induced by source paper "a new bound for 3 satisfiable maxsat and its algorithmic application"):
  with members:
    - "parameterized complexity of maxsat above average"
    - "a new lower bound on the maximum number of satisfied clauses in max sat and its algorithmic application"
    - "solving max r sat above a tight lower bound"
    - "note on max lin 2 above average"

Connected through hyperedge HE-4 (induced by source paper "max cut parameterized above the edwards erd h o s bound"):
  with members:
    - "maximum balanced subgraph problem parameterized above lower bound"
    - "note on maximal bisection above tight lower bound"

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.DS(Data Structures and Algorithms)