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Constructing energy-efficient mixed-precision neural networks through principal component analysis for edge intelligence.

, , , , and . Nat. Mach. Intell., 2 (1): 43-55 (2020)

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On the Noise Stability and Robustness of Adversarially Trained Networks on NVM Crossbars., , , and . CoRR, (2021)Revisiting Stochastic Computing in the Era of Nanoscale Nonvolatile Technologies., , , , , , , , , and 1 other author(s). IEEE Trans. Very Large Scale Integr. Syst., 28 (12): 2481-2494 (2020)Technology Aware Training in Memristive Neuromorphic Systems based on non-ideal Synaptic Crossbars., , and . CoRR, (2017)Tree-CNN: A hierarchical Deep Convolutional Neural Network for incremental learning., , and . Neural Networks, (2020)Neural Networks at the Edge., , , , , , and . SMARTCOMP, page 45-50. IEEE, (2019)Robustness Hidden in Plain Sight: Can Analog Computing Defend Against Adversarial Attacks?, , , and . CoRR, (2020)Embracing Stochasticity to Enable Neuromorphic Computing at the Edge., , , and . IEEE Des. Test, 38 (6): 28-35 (2021)On the Intrinsic Robustness of NVM Crossbars Against Adversarial Attacks., , , and . DAC, page 565-570. IEEE, (2021)Efficient Hybrid Network Architectures for Extremely Quantized Neural Networks Enabling Intelligence at the Edge., , , and . CoRR, (2019)Constructing energy-efficient mixed-precision neural networks through principal component analysis for edge intelligence., , , , and . Nat. Mach. Intell., 2 (1): 43-55 (2020)