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: "max cut under graph constraints"
  Abstract: An instance of the graph-constrained max-cut $$\mathsf {GCMC}$$ problem consists of i an undirected graph $$G=V,E$$ and ii edge-weights $$c:{V\atopwithdelims 2} \rightarrow \mathbb {R}_+$$ on a complete undirected graph. The objective is to find a subset $$S \subseteq V$$ of vertices satisfying some graph-based constraint in G that maximizes the weight $$\sum _{u\in S, v\not \in S} c_{uv}$$ of edges in the cut $$S,V{\setminus } S$$. The types of graph constraints we can handle include independent set, vertex cover, dominating set and connectivity.#R##N##R##N#Our main results are for the case when G is a graph with bounded treewidth, where we obtain a $$\frac{1}{2}$$-approximation algorithm. Our algorithm uses an LP relaxation based on the Sherali-Adams hierarchy. It can handle any graph constraint for which there is a certain type of dynamic program that exactly optimizes linear objectives.#R##N##R##N#Using known decomposition results, these imply essentially the same approximation ratio for $$\mathsf {GCMC}$$ under constraints such as independent set, dominating set and connectivity on a planar graph G more generally for bounded-genus or excluded-minor graphs.

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)