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 "circulation control for faster minimum cost flow in unit capacity graphs"):
  Abstract: We present an $m^{11/8+o(1)} \log W$-time algorithm for solving the minimum cost flow problem in graphs with unit capacity, where $W$ is the absolute maximum weight of an edge in the graph. For sparse graphs, this improves over the best known running time for this problem and, by well-known reductions, also implies improved running times for the shortest path problem with negative weights, minimum cost bipartite $\boldsymbol{\mathit{b}}$-matching when $\|\boldsymbol{\mathit{b}}\|_1 = O(m)$, and recovers the running time of the currently fastest algorithm for maximum flow in graphs with unit capacities (Liu-Sidford). #R##N#Our algorithm relies on developing an interior point method--based framework which acts on the space of circulations in the underlying graph. From the combinatorial point of view, this framework can be viewed as iteratively improving the cost of a suboptimal solution by pushing flow around circulations. These circulations are derived by computing a regularized version of the standard Newton step, which can be done efficiently due to recent developments on computing $\ell_p$-norm minimizing flows (Kyng-Peng-Sachdeva-Wang). We obtain our faster algorithm by combining this approach with a customized preconditioning method, which aims to ensure that the graph on which these circulations are computed has sufficiently large conductance.

Includes members:
  Member "faster p norm minimizing flows via smoothed q norm problems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "faster divergence maximization for faster maximum flow")
  Member "faster energy maximization for faster maximum flow":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "faster divergence maximization for faster maximum flow")
  Member "flows in almost linear time via adaptive preconditioning":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "faster divergence maximization for faster maximum flow")
  Member "computing maximum flow with augmenting electrical flows":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "faster divergence maximization for faster maximum flow")
  Member "approximate undirected maximum flows in o m polylog n time":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "faster divergence maximization for faster maximum flow")
  Member "an almost linear time algorithm for approximate max flow in undirected graphs and its multicommodity generalizations":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "faster divergence maximization for faster maximum flow")
  Member "an efficient parallel solver for sdd linear systems":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "fully dynamic spectral vertex sparsifiers and applications")
  Member "a simple combinatorial algorithm for solving sdd systems in nearly linear time":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "spectral sparsification via bounded independence sampling")

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)