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All-in-One: A Highly Representative DNN Pruning Framework for Edge Devices with Dynamic Power Management.

, , , , , , , , and . ICCAD, page 133:1-133:9. ACM, (2022)

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Achieving on-Mobile Real-Time Super-Resolution with Neural Architecture and Pruning Search., , , , , , , , , and 2 other author(s). ICCV, page 4801-4811. IEEE, (2021)MOC: Multi-Objective Mobile CPU-GPU Co-Optimization for Power-Efficient DNN Inference., , , , , , , and . ICCAD, page 1-10. IEEE, (2023)Research on Characteristics of Chinese Herbal Medicine Compounds Based on Bisecting k-Means Algorithm., , , , , and . FSDM, volume 331 of Frontiers in Artificial Intelligence and Applications, page 351-359. IOS Press, (2020)All-in-One: A Highly Representative DNN Pruning Framework for Edge Devices with Dynamic Power Management., , , , , , , , and . ICCAD, page 133:1-133:9. ACM, (2022)DACO: Pursuing Ultra-low Power Consumption via DNN-Adaptive CPU-GPU CO-optimization on Mobile Devices., , , , , , , , and . DATE, page 1-2. IEEE, (2024)Preliminary Experimental Results of Context-Aware Teams of Multiple Autonomous Agents Operating under Constrained Communications., , , , , , , , , and 4 other author(s). Robotics, 11 (5): 94 (2022)You Already Have It: A Generator-Free Low-Precision DNN Training Framework Using Stochastic Rounding., , , , , , , , , and 4 other author(s). ECCV (12), volume 13672 of Lecture Notes in Computer Science, page 34-51. Springer, (2022)TOUGH2-PETSc: A Parallel Solver for TOUGH2., , and . PDCAT, page 174-179. IEEE Computer Society, (2014)Digital Avatars: Framework Development and Their Evaluation., , , , , , , , , and 2 other author(s). CoRR, (2024)Compiler-Aware Neural Architecture Search for On-Mobile Real-time Super-Resolution., , , , , , , , , and . ECCV (19), volume 13679 of Lecture Notes in Computer Science, page 92-111. Springer, (2022)