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Performance optimization of continuous-time Markov control processes based on performance potentials.

, , and . Int. J. Systems Science, 34 (1): 63-71 (2003)

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Performance Optimization of Semi-Markov Decision Processes with Discounted-cost Criteria., , , and . Eur. J. Control, 14 (3): 213-222 (2008)Pruning filters with L1-norm and capped L1-norm for CNN compression., , , , and . Appl. Intell., 51 (2): 1152-1160 (2021)Weight-dependent Gates for Network Pruning., , , , , , and . CoRR, (2020)Feature Reaggregation Network for Crowd Counting., , , , and . ICAIP, page 89-94. ACM, (2020)Simulation-Based Optimization of Singularly Perturbed Markov Reward Processes with States Aggregation., , and . ICIC (2), volume 3645 of Lecture Notes in Computer Science, page 129-138. Springer, (2005)Using Feature Entropy to Guide Filter Pruning for Efficient Convolutional Networks., , , , and . ICANN (2), volume 11728 of Lecture Notes in Computer Science, page 263-274. Springer, (2019)VisDrone-CC2021: The Vision Meets Drone Crowd Counting Challenge Results., , , , , , , , , and 29 other author(s). ICCVW, page 2830-2838. IEEE, (2021)Modeling and Analysis for Streaming Service Systems., , and . Int. J. Autom. Comput., 11 (4): 449-458 (2014)Partially Observable Markov Decision Processes and Performance Sensitivity Analysis., , and . IEEE Trans. Syst. Man Cybern. Part B, 38 (6): 1645-1651 (2008)CFFNet: Coordinated feature fusion network for crowd counting., , , , and . Image Vis. Comput., (2021)