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 "beyond no regret competitive control via online optimization with memory"):
  Abstract: This paper studies online control with adversarial disturbances using tools from online optimization with memory. Most work that bridges learning and control theory focuses on designing policies that are no-regret with respect to the best static linear controller in hindsight. However, the optimal offline controller can have orders-of-magnitude lower cost than the best linear controller. We instead focus on achieving constant competitive ratio compared to the offline optimal controller, which need not be linear or static. We provide a novel reduction from online control of a class of controllable systems to online convex optimization with memory. We then design a new algorithm for online convex optimization with memory, Optimistic Regularized Online Balanced Descent, that has a constant, dimension-free competitive ratio. This result, in turn, leads to a new constant-competitive approach for online control.

Includes members:
  Member "chasing convex bodies optimally":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "the online min sum set cover problem")
  Member "robust regression for safe exploration in control":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "deep learning tubes for tube mpc")
  Member "episodic learning with control lyapunov functions for uncertain robotic systems":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "learning stable deep dynamics models")
  Member "competitive online optimization under inventory constraints":
    also connected through other hyperedges:
      (none)
  Member "online control with adversarial disturbances":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "improper learning for non stochastic control")
  Member "beyond online balanced descent an optimal algorithm for smoothed online optimization":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "online optimization with predictions and non convex losses")
  Member "neural swarm decentralized close proximity multirotor controlusing learned interactions":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "glas global to local safe autonomy synthesis for multi robot motion planning with end to end learning")
  Member "online inventory management with application to energy procurement in data centers":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "learning assisted competitive algorithms for peak aware energy scheduling")

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.LG(Machine Learning)