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: "learning assisted competitive algorithms for peak aware energy scheduling"
  Abstract: In this paper, we study the peak-aware energy scheduling problem using the competitive framework with machine learning prediction. With the uncertainty of energy demand as the fundamental challenge, the goal is to schedule the energy output of local generation units such that the electricity bill is minimized. While this problem has been tackled using classic competitive design with worst-case guarantee, the goal of this paper is to develop learning-assisted competitive algorithms to improve the performance in a provable manner. We develop two deterministic and randomized algorithms that are provably robust against the poor performance of learning prediction, however, achieve the optimal performance as the error of prediction goes to zero. Extensive experiments using real data traces verify our theoretical observations and show 15.13% improved performance against pure online algorithms.

Connected through hyperedge HE-1 (induced by source paper "online algorithms for multi shop ski rental with machine learned predictions"):
  with members:
    - "optimal algorithms for ski rental with soft machine learned predictions"
    - "a model for learned bloom filters and optimizing by sandwiching"
    - "online computation with untrusted advice"
    - "competitive caching with machine learned advice"
    - "revenue optimization with approximate bid predictions"
    - "the multi shop ski rental problem"
    - "rent lease or buy randomized algorithms for multislope ski rental"

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)