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 "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.

Includes members:
  Member "approximation algorithms for connected maximum cut and related problems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "parameterized algorithms for maximum cut with connectivity constraints")
  Member "sparsest cut on bounded treewidth graphs algorithms and hardness results":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "on the parameterized complexity of sparsest cut and small set expansion problems")
  Member "submodular function maximization via the multilinear relaxation and contention resolution schemes":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "approximability of monotone submodular function maximization under cardinality and matroid constraints in the streaming model")

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.DS(Data Structures and Algorithms)