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GARLSched: Generative adversarial deep reinforcement learning task scheduling optimization for large-scale high performance computing systems.

, , , , and . Future Gener. Comput. Syst., (2022)

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Exploiting fast hardware floating point in high precision computation., and . ISSAC, page 111-118. ACM, (2003)Research on the selection of strategic supplier based on grey relation and multi level fuzzy evaluation in the electronics industry., and . SMC, page 12-16. IEEE, (2012)Qualitative Analysis for a Kind of Predator-Prey Model of Holling III-Function Response with Nonlinear Density Dependent., , and . CIS, page 1532-1535. IEEE Computer Society, (2011)Distributed power self-optimization with convex pricing in dense femtocell networks via an exact potential game., , , , and . PIMRC, page 1919-1923. IEEE, (2013)Extraction and Analysis of Risk Factors from Chinese Railway Accident Reports., , and . ITSC, page 869-874. IEEE, (2019)Dynamic Clustering Based Sub-Band Allocation in Dense Femtocell Environments., , , and . VTC Spring, page 1-5. IEEE, (2012)A benchmark approach and its toolkit for online scheduling of multiple deadline-constrained workflows in big-data processing systems., , , , and . Future Gener. Comput. Syst., (2018)Model topology formulation for nonlinear dynamic behavioral modeling., , , and . CICC, page 721-724. IEEE, (2005)Adaptive neural time-varying full-state constraints quantized consensus control for nonlinear multiagent networks systems without feasibility conditions., , and . Neural Comput. Appl., 35 (22): 16457-16472 (August 2023)A switch-controlled multimode narrowband receiver RF front-end., , , , and . Int. J. Commun. Syst., (2019)