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Beyond charge-based computation: Boolean and non-Boolean computing with spin torque devices., , , and . ISLPED, page 139-142. IEEE, (2013)Defend Deep Neural Networks Against Adversarial Examples via Fixed andDynamic Quantized Activation Functions., , , and . CoRR, (2018)Exploring Boolean and Non-Boolean Computing Applications of Spin Torque Devices., , , and . CoRR, (2013)Ultra-low Energy, High-Performance Dynamic Resistive Threshold Logic., , and . CoRR, (2013)Defense-Net: Defend Against a Wide Range of Adversarial Attacks through Adversarial Detector., and . ISVLSI, page 332-337. IEEE, (2019)Representable Matrices: Enabling High Accuracy Analog Computation for Inference of DNNs using Memristors., , , and . CoRR, (2019)ReDRAM: A Reconfigurable Processing-in-DRAM Platform for Accelerating Bulk Bit-Wise Operations., and . ICCAD, page 1-8. ACM, (2019)Parametric Noise Injection: Trainable Randomness to Improve Deep Neural Network Robustness against Adversarial Attack., , and . CoRR, (2018)Processing-In-Memory Acceleration of Convolutional Neural Networks for Energy-Effciency, and Power-Intermittency Resilience., , , and . ISQED, page 8-13. IEEE, (2019)Leveraging All-Spin Logic to Improve Hardware Security., , and . ACM Great Lakes Symposium on VLSI, page 491-494. ACM, (2017)