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 "a learning theoretic approach to energy harvesting communication system optimization"):
  Abstract: A point-to-point wireless communication system in which the transmitter is equipped with an energy harvesting device and a rechargeable battery, is studied. Both the energy and the data arrivals at the transmitter are modeled as Markov processes. Delay-limited communication is considered assuming that the underlying channel is block fading with memory, and the instantaneous channel state information is available at both the transmitter and the receiver. The expected total transmitted data during the transmitter's activation time is maximized under three different sets of assumptions regarding the information available at the transmitter about the underlying stochastic processes. A learning theoretic approach is introduced, which does not assume any a priori information on the Markov processes governing the communication system. In addition, online and offline optimization problems are studied for the same setting. Full statistical knowledge and causal information on the realizations of the underlying stochastic processes are assumed in the online optimization problem, while the offline optimization problem assumes non-causal knowledge of the realizations in advance. Comparing the optimal solutions in all three frameworks, the performance loss due to the lack of the transmitter's information regarding the behaviors of the underlying Markov processes is quantified.

Includes members:
  Member "throughput maximization for the gaussian relay channel with energy harvesting constraints":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "timely updates in energy harvesting two hop networks offline and online policies")
  Member "on the complexity of policy iteration":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "solving discounted stochastic two player games with near optimal time and sample complexity")
  Member "throughput maximization for an energy harvesting communication system with processing cost":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "online policies for throughput maximization of energy constrained wireless powered communication systems")
  Member "sum rate optimal power policies for energy harvesting transmitters in an interference channel":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "age minimal online policies for energy harvesting sensors with random battery recharges")
  Member "two hop communication with energy harvesting":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "timely updates in energy harvesting two hop networks offline and online policies")
  Member "optimal energy allocation for wireless communications with energy harvesting constraints":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "optimal energy allocation and task offloading policy for wireless powered mobile edge computing systems")
  Member "a general framework for the optimization of energy harvesting communication systems with battery imperfections":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "on the energy and data storage management in energy harvesting wireless communications")
  Member "transmission with energy harvesting nodes in fading wireless channels optimal policies":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "closed form analysis of non linear age of information in status updates with an energy harvesting transmitter")

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)