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 "algorithms to approximate column sparse packing problems"):
  Abstract: Column-sparse packing problems arise in several contexts in both deterministic and stochastic discrete optimization. We present two unifying ideas, (non-uniform) attenuation and multiple-chance algorithms, to obtain improved approximation algorithms for some well-known families of such problems. As three main examples, we attain the integrality gap, up to lower-order terms, for known LP relaxations for k-column sparse packing integer programs (Bansal et al., Theory of Computing, 2012) and stochastic k-set packing (Bansal et al., Algorithmica, 2012), and go "half the remaining distance" to optimal for a major integrality-gap conjecture of Furedi, Kahn and Seymour on hypergraph matching (Combinatorica, 1993).

Includes members:
  Member "attenuate locally win globally an attenuation based framework for online stochastic matching with timeouts":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "vertex weighted online stochastic matching with patience constraints")
  Member "random order contention resolution schemes":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "optimal single choice prophet inequalities from samples")
  Member "adaptivity gaps for stochastic probing submodular and xos functions":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "pandora s box problem with order constraints")
  Member "improved algorithmic bounds for discrepancy of sparse set systems":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "an algorithm for koml os conjecture matching banaszczyk s bound")
  Member "deterministic discrepancy minimization via the multiplicative weight update method":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "online vector balancing and geometric discrepancy")
  Member "constrained submodular maximization via a non symmetric technique":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "non monotone submodular maximization with nearly optimal adaptivity and query complexity")
  Member "constrained submodular maximization beyond 1 e":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "optimal streaming algorithms for submodular maximization with cardinality constraints")
  Member "non negative submodular stochastic probing via stochastic contention resolution schemes":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "an optimal monotone contention resolution scheme for bipartite matchings via a polyhedral viewpoint")

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)