human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "better algorithms for unfair metrical task systems and applications"
  Abstract: Unfair metrical task systems are a generalization of online metrical task systems. In this paper we introduce new techniques to combine algorithms for unfair metrical task systems and apply these techniques to obtain improved randomized online algorithms for metrical task systems on arbitrary metric spaces.

Connected through hyperedge HE-1 (induced by source paper "competitive ratio versus regret minimization achieving the best of both worlds"):
  with members:
    - "online learning over a finite action set with limited switching"
    - "k server via multiscale entropic regularization"
    - "a tale of two metrics simultaneous bounds on competitiveness and regret"
    - "online optimization competing with dynamic comparators"
    - "strongly adaptive online learning"
    - "the computational power of optimization in online learning"
    - "achieving all with no parameters adaptive normalhedge"
    - "an improved approximation for k median and positive correlation in budgeted optimization"

Connected through hyperedge HE-2 (induced by source paper "competitive online optimization under inventory constraints"):
  with members:
    - "balancing cost and dissatisfaction in online ev charging under real time pricing"
    - "nested convex bodies are chaseable"
    - "beyond matroids secretary problem and prophet inequality with general constraints"
    - "online offering strategies for storage assisted renewable power producer in hour ahead market"
    - "online convex optimization using predictions"
    - "a tale of two metrics simultaneous bounds on competitiveness and regret"
    - "peak aware online economic dispatching for microgrids"
    - "the submodular secretary problem goes linear"

Connected through hyperedge HE-3 (induced by source paper "parametrized metrical task systems"):
  with members:
    - "metrical task systems on trees via mirror descent and unfair gluing"
    - "metrical service systems with multiple servers"
    - "competitive paging algorithms"

Connected through hyperedge HE-4 (induced by source paper "pure entropic regularization for metrical task systems"):
  with members:
    - "metrical task systems on trees via mirror descent and unfair gluing"
    - "regret analysis of stochastic and nonstochastic multi armed bandit problems"

Connected through hyperedge HE-5 (induced by source paper "metrical task systems on trees via mirror descent and unfair gluing"):
  with members:
    - "k server via multiscale entropic regularization"

Connected through hyperedge HE-6 (induced by source paper "nested convex bodies are chaseable"):
  with members:
    - "chasing convex bodies optimally"
    - "chasing convex bodies with linear competitive ratio"
    - "a nearly linear bound for chasing nested convex bodies"
    - "competitively chasing convex bodies"
    - "chasing nested convex bodies nearly optimally"
    - "a tale of two metrics simultaneous bounds on competitiveness and regret"
    - "the generalized work function algorithm is competitive for the generalized 2 server problem"
    - "ramsey type theorems for metric spaces with applications to online problems"

Connected through hyperedge HE-7 (induced by source paper "stochastic k server how should uber work"):
  with members:
    - "beating 1 frac 1 e for ordered prophets"
    - "a polylogarithmic competitive algorithm for the k server problem"
    - "adcell ad allocation in cellular networks"
    - "truly online paging with locality of reference"
    - "competitive paging algorithms"

Connected through hyperedge HE-8 (induced by source paper "a competitive ratio approximation scheme for the k server problem in fixed finite metrics"):
  with members:
    - "competitive ratio approximation schemes for minimizing the makespan in the online list model"
    - "randomized online computation with high probability guarantees"
    - "a new approach to online scheduling approximating the optimal competitive ratio"
    - "a polylogarithmic competitive algorithm for the k server problem"
    - "ramsey type theorems for metric spaces with applications to online problems"
    - "competitive paging algorithms"

Question: Please tell me which class the center node 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)