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 "fully dynamic bin packing with limited repacking"):
  Abstract: We study the classic Bin Packing problem in a fully-dynamic setting, where new items can arrive and old items may depart. We want algorithms with low asymptotic competitive ratio \emph{while repacking items sparingly} between updates. Formally, each item $i$ has a \emph{movement cost} $c_i\geq 0$, and we want to use $\alpha \cdot OPT$ bins and incur a movement cost $\gamma\cdot c_i$, either in the worst case, or in an amortized sense, for $\alpha, \gamma$ as small as possible. We call $\gamma$ the \emph{recourse} of the algorithm. This is motivated by cloud storage applications, where fully-dynamic Bin Packing models the problem of data backup to minimize the number of disks used, as well as communication incurred in moving file backups between disks. Since the set of files changes over time, we could recompute a solution periodically from scratch, but this would give a high number of disk rewrites, incurring a high energy cost and possible wear and tear of the disks. In this work, we present optimal tradeoffs between number of bins used and number of items repacked, as well as natural extensions of the latter measure.

Includes members:
  Member "a new and improved algorithm for online bin packing":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "streaming algorithms for bin packing and vector scheduling")
  Member "a tight approximation for fully dynamic bin packing without bundling":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "fully dynamic bin packing revisited")
  Member "beating the harmonic lower bound for online bin packing":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "parallel online algorithms for the bin packing problem")
  Member "a logarithmic additive integrality gap for bin packing":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "streaming algorithms for bin packing and vector scheduling")
  Member "fully dynamic bin packing revisited":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "robust online algorithms for dynamic problems")
  Member "a robust afptas for online bin packing with polynomial migration":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "robust online algorithms for dynamic problems")

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)