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 "online bin covering with advice"):
  Abstract: The bin covering problem asks for covering a maximum number of bins with an online sequence of $n$ items of different sizes in the range $(0,1]$; a bin is said to be covered if it receives items of total size at least 1. We study this problem in the advice setting and provide tight bounds for the size of advice required to achieve optimal solutions. Moreover, we show that any algorithm with advice of size $o(\log \log n)$ has a competitive ratio of at most 0.5. In other words, advice of size $o(\log \log n)$ is useless for improving the competitive ratio of 0.5, attainable by an online algorithm without advice. This result highlights a difference between the bin covering and the bin packing problems in the advice model: for the bin packing problem, there are several algorithms with advice of constant size that outperform online algorithms without advice. Furthermore, we show that advice of size $O(\log \log n)$ is sufficient to achieve a competitive ratio that is arbitrarily close to $0.53\bar{3}$ and hence strictly better than the best ratio $0.5$ attainable by purely online algorithms. The technicalities involved in introducing and analyzing this algorithm are quite different from the existing results for the bin packing problem and confirm the different nature of these two problems. Finally, we show that a linear number of bits of advice is necessary to achieve any competitive ratio better than 15/16 for the online bin covering problem.

Includes members:
  Member "a new lower bound for classic online bin packing":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "parallel online algorithms for the bin packing problem")
  Member "a new and improved algorithm for online bin packing":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "streaming algorithms for bin packing and vector scheduling")
  Member "a simple ptas for the dual bin packing problem and advice complexity of its online version":
    also connected through other hyperedges:
      (none)
  Member "on the power of advice and randomization for online bipartite matching":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "temporal matching")
  Member "randomization can be as helpful as a glimpse of the future in online computation":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "tight bounds for online edge coloring")
  Member "a logarithmic additive integrality gap for bin packing":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "streaming algorithms for bin packing and vector scheduling")
  Member "online algorithms with advice for bin packing and scheduling problems":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "parallel online algorithms for the bin packing problem")
  Member "approximating bin packing within o log opt log log opt bins":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "an optimal algorithm for 1 d cutting stock problem")

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)