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An area and energy efficient design of domain-wall memory-based deep convolutional neural networks using stochastic computing., , , , , , , и . ISQED, стр. 314-321. IEEE, (2018)Tiny but Accurate: A Pruned, Quantized and Optimized Memristor Crossbar Framework for Ultra Efficient DNN Implementation., , , , , , , , и . CoRR, (2019)Achieving Real-Time Object Detection on MobileDevices with Neural Pruning Search., , , , , , и . CoRR, (2021)MTS-LOF: Medical Time-Series Representation Learning via Occlusion-Invariant Features., , , , и . CoRR, (2023)Hardware-efficient stochastic rounding unit design for DNN training: late breaking results., , , , , , , , , и 2 other автор(ы). DAC, стр. 1396-1397. ACM, (2022)Fault-Tolerant Deep Neural Networks for Processing-In-Memory based Autonomous Edge Systems., , , , , и . DATE, стр. 424-429. IEEE, (2022)Real-Time Mobile Acceleration of DNNs: From Computer Vision to Medical Applications., , , , , , , , и . ASP-DAC, стр. 581-586. ACM, (2021)MEST: Accurate and Fast Memory-Economic Sparse Training Framework on the Edge., , , , , , , , , и 6 other автор(ы). NeurIPS, стр. 20838-20850. (2021)A DNN Compression Framework for SOT-MRAM-based Processing-In-Memory Engine., , , , , и . SoCC, стр. 37-42. IEEE, (2020)Teachers Do More Than Teach: Compressing Image-to-Image Models., , , , , , и . CVPR, стр. 13600-13611. Computer Vision Foundation / IEEE, (2021)