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 "near linear time approximation schemes for uncapacitated and capacitated b matching problems in nonbipartite graphs"):
  Abstract: We present the first near optimal approximation schemes for the #R##N#maximum weighted (uncapacitated or capacitated) $b$--matching #R##N#problems for non-bipartite graphs that run in time (near) linear in #R##N#the number of edges. For any $\delta>3/\sqrt{n}$ the algorithm #R##N#produces a $(1-\delta)$ approximation in $O(m \poly(\delta^{-1},\log #R##N#n))$ time. We provide fractional solutions for the standard linear #R##N#programming formulations for these problems and subsequently also #R##N#provide (near) linear time approximation schemes #R##N#for rounding the fractional solutions. #R##N#Through these problems as a vehicle, we also present several ideas #R##N#in the context of solving linear programs approximately using fast #R##N#primal-dual algorithms. First, even though the dual of these #R##N#problems have exponentially many variables and an efficient exact #R##N#computation of dual weights is infeasible, we show that we can #R##N#efficiently compute and use a sparse approximation of the dual #R##N#weights using a combination of (i) adding perturbation to the #R##N#constraints of the polytope and (ii) amplification followed by #R##N#thresholding of the dual weights. Second, we show that #R##N#approximation algorithms can be used to reduce the width of the #R##N#formulation, and faster convergence.

Includes members:
  Member "faster approximate multicommodity flow using quadratically coupled flows":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "faster divergence maximization for faster maximum flow")
  Member "laminar families and metric embeddings non bipartite maximum matching problem in the semi streaming model":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "space efficient approximation to maximum matching size from uniform edge samples")
  Member "scaling algorithms for approximate and exact maximum weight matching":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "faster maximium priority matchings in bipartite graphs")
  Member "linear programming in the semi streaming model with application to the maximum matching problem":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "two player hidden pointer chasing and multi pass lower bounds in turnstile streams")
  Member "electrical flows laplacian systems and faster approximation of maximum flow in undirected graphs":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a spectral approach to network design")

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)