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Machine learning approach to predict center of pressure trajectories in a complete gait cycle: a feedforward neural network vs. LSTM network.

, , , , and . Medical Biol. Eng. Comput., 57 (12): 2693-2703 (2019)

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Towards Machine Learning with Zero Real-World Data., , and . WearSys@MobiSys, page 41-46. ACM, (2019)Quantum-Assisted Decoding for Non-Binary Low-Density Parity-Check Codes., , and . ICTC, page 1594-1599. IEEE, (2021)A Study on Thermal Issues in Mobile Extended Reality Applications., , and . SenSys, page 797-799. ACM, (2022)Low-Complexity Decoding Algorithm Utilizing Degeneracy for Quantum LDPC Codes., , and . MILCOM, page 115-120. IEEE, (2023)Improved Approximation Algorithm for Connected Facility Location Problems., , and . COCOA, volume 4616 of Lecture Notes in Computer Science, page 311-322. Springer, (2007)The Balloon Popping Problem Revisited: Lower and Upper Bounds., and . SAGT, volume 5814 of Lecture Notes in Computer Science, page 147-158. Springer, (2009)Aggressive SRAM Voltage Scaling and Error Mitigation for Approximate DNN Inference., , , and . SmartWear@MobiCom, page 28-34. ACM, (2023)Machine Learning without Real-world Data., , and . MobiSys, page 643-644. ACM, (2019)Simultaneous Sporadic Sensor Anomaly Detection for Smart Homes., , , and . SenSys, page 1061-1066. ACM, (2022)Episodic Memory Reader: Learning What to Remember for Question Answering from Streaming Data., , , and . ACL (1), page 4407-4417. Association for Computational Linguistics, (2019)