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Federated Dynamic Sparse Training: Computing Less, Communicating Less, Yet Learning Better., , , and . CoRR, (2021)Robot Orientation Learning Based on Interaction Primitives for Human-Robot Collaboration., , , , , and . RCAR, page 701-706. IEEE, (2023)SmartExchange: Trading Higher-cost Memory Storage/Access for Lower-cost Computation., , , , , , , , and . ISCA, page 954-967. IEEE, (2020)E2-Train: Training State-of-the-art CNNs with Over 80% Energy Savings., , , , , , and . NeurIPS, page 5139-5151. (2019)Model elasticity for hardware heterogeneity in federated learning systems., , , and . FedEdge@MobiCom, page 19-24. ACM, (2022)Can We Gain More from Orthogonality Regularizations in Training Deep CNNs?, , and . CoRR, (2018)Drawing Early-Bird Tickets: Toward More Efficient Training of Deep Networks., , , , , , , , and . ICLR, OpenReview.net, (2020)On Performance Comparison of Real and Synthetic Iris Images., , and . ICIP, page 305-308. IEEE, (2006)A Novel Local Binary Temporal Convolutional Neural Network for Bearing Fault Diagnosis., , , , and . IEEE Trans. Instrum. Meas., (2023)Deep Transfer Learning for Bearing Fault Diagnosis: A Systematic Review Since 2016., , , , , and . IEEE Trans. Instrum. Meas., (2023)