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Efficient Personalized Learning for Wearable Health Applications using HyperDimensional Computing., , , , , , and . CoRR, (2022)On the feasibility of SISO control-theoretic DVFS for power capping in CMPs., , , and . Microprocess. Microsystems, (2018)Partition Pruning: Parallelization-Aware Pruning for Dense Neural Networks., , , and . PDP, page 307-311. IEEE, (2020)Exploring Energy Efficient Architectures for RLWE Lattice-Based Cryptography., , , and . J. Signal Process. Syst., 93 (10): 1139-1148 (2021)Hybrid Learning for Orchestrating Deep Learning Inference in Multi-user Edge-cloud Networks., , , , , , and . ISQED, page 1-6. IEEE, (2022)Partition Pruning: Parallelization-Aware Pruning for Deep Neural Networks., , , , and . CoRR, (2019)Edge-centric Optimization of Multi-modal ML-driven eHealth Applications., , , , , , and . CoRR, (2022)Exploring Energy Efficient Quantum-resistant Signal Processing Using Array Processors., , , and . IACR Cryptol. ePrint Arch., (2019)Dependability evaluation of SISO control-theoretic power managers for processor architectures., , , and . NORCAS, page 1-6. IEEE, (2017)An Edge-Assisted and Smart System for Real-Time Pain Monitoring., , , , , and . CHASE, page 47-52. IEEE, (2019)