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 "chasing convex bodies with linear competitive ratio"):
  Abstract: We study the problem of chasing convex bodies online: given a sequence of convex bodies $K_t\subseteq \mathbb{R}^d$ the algorithm must respond with points $x_t\in K_t$ in an online fashion (i.e., $x_t$ is chosen before $K_{t+1}$ is revealed). The objective is to minimize the total distance between successive points in this sequence. Recently, Bubeck et al. (STOC 2019) gave a $2^{O(d)}$-competitive algorithm for this problem. We give an algorithm that is $O(\min(d, \sqrt{d \log T}))$-competitive for any sequence of length $T$.

Includes members:
  Member "beyond online balanced descent an optimal algorithm for smoothed online optimization":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "beyond no regret competitive control via online optimization with memory")
  Member "a nearly linear bound for chasing nested convex bodies":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "path length bounds for gradient descent and flow")
  Member "competitively chasing convex bodies":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "beyond no regret competitive control via online optimization with memory")
  Member "smoothed online convex optimization in high dimensions via online balanced descent":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "understand dynamic regret with switching cost for online decision making")
  Member "chasing nested convex bodies nearly optimally":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "path length bounds for gradient descent and flow")
  Member "nested convex bodies are chaseable":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "path length bounds for gradient descent and flow")
  Member "the generalized work function algorithm is competitive for the generalized 2 server problem":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "the online min sum set cover 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)