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6.7ms on Mobile with over 78% ImageNet Accuracy: Unified Network Pruning and Architecture Search for Beyond Real-Time Mobile Acceleration., , , , , , , , , and 6 other author(s). CoRR, (2020)BLCR: Towards Real-time DNN Execution with Block-based Reweighted Pruning., , , , , , , , , and 3 other author(s). ISQED, page 1-8. IEEE, (2022)Chic: experience-driven scheduling in machine learning clusters., , , and . IWQoS, page 30:1-30:10. ACM, (2019)Condense: A Framework for Device and Frequency Adaptive Neural Network Models on the Edge., , , , , , , , and . DAC, page 1-6. IEEE, (2023)Research on Multi-UAV Loading Multi-type Sensors Cooperative Reconnaissance Task Planning Based on Genetic Algorithm., , , , and . ICIC (1), volume 10361 of Lecture Notes in Computer Science, page 485-500. Springer, (2017)DualHSIC: HSIC-Bottleneck and Alignment for Continual Learning., , , , , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 36578-36592. PMLR, (2023)Representation Learning on Spatial Networks., and . NeurIPS, page 2303-2318. (2021)A Unified DNN Weight Pruning Framework Using Reweighted Optimization Methods., , , , , , and . DAC, page 493-498. IEEE, (2021)Universal Approximation Property and Equivalence of Stochastic Computing-Based Neural Networks and Binary Neural Networks., , , , , , , , and . AAAI, page 5369-5376. AAAI Press, (2019)Towards Real-Time DNN Inference on Mobile Platforms with Model Pruning and Compiler Optimization., , , , , and . IJCAI, page 5306-5308. ijcai.org, (2020)Demo.