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Design Automation for Binarized Neural Networks: A Quantum Leap Opportunity?, , and . CoRR, (2017)PULP-TrainLib: Enabling On-Device Training for RISC-V Multi-core MCUs Through Performance-Driven Autotuning., , , , , and . SAMOS, volume 13511 of Lecture Notes in Computer Science, page 200-216. Springer, (2022)Bio-inspired Autonomous Exploration Policies with CNN-based Object Detection on Nano-drones., , , , , and . DATE, page 1-6. IEEE, (2023)Memory-Latency-Accuracy Trade-Offs for Continual Learning on a RISC-V Extreme-Edge Node., , , , , , , and . SiPS, page 1-6. IEEE, (2020)Memory-Driven Mixed Low Precision Quantization For Enabling Deep Network Inference On Microcontrollers., , and . CoRR, (2019)Robust navigation with tinyML for autonomous mini-vehicles., , , , , , and . CoRR, (2020)PULP-NN: A Computing Library for Quantized Neural Network inference at the edge on RISC-V Based Parallel Ultra Low Power Clusters., , , , and . ICECS, page 33-36. IEEE, (2019)Accelerating RNN-Based Speech Enhancement on a Multi-core MCU with Mixed FP16-INT8 Post-training Quantization., , , , and . PKDD/ECML Workshops (1), volume 1752 of Communications in Computer and Information Science, page 606-617. Springer, (2022)Integer-Only Approximated MFCC for Ultra-Low Power Audio NN Processing on Multi-Core MCUs., , , and . AICAS, page 1-4. IEEE, (2021)On-Device Domain Learning for Keyword Spotting on Low-Power Extreme Edge Embedded Systems., , , , and . CoRR, (2024)