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Low-Power Manycore Accelerator for Personalized Biomedical Applications.

, , , , and . ACM Great Lakes Symposium on VLSI, page 63-68. ACM, (2016)

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Low-Power Manycore Accelerator for Personalized Biomedical Applications., , , , and . ACM Great Lakes Symposium on VLSI, page 63-68. ACM, (2016)Task Scheduling for GPU Accelerated Hybrid OLAP Systems with Multi-core Support and Text-to-Integer Translation., , , and . IPDPS Workshops, page 1987-1996. IEEE Computer Society, (2012)CS-Based Secured Big Data Processing on FPGA., , , and . FCCM, page 201. IEEE Computer Society, (2016)PACENet: Energy efficient acceleration for convolutional network on embedded platform., , , , and . ISCAS, page 1-4. IEEE, (2017)Task scheduling for GPU accelerated OLAP systems., , , and . CASCON, page 107-119. IBM / ACM, (2011)Statistical estimation of T1 relaxation times using conventional magnetic resonance imaging., , , , , , , and . NeuroImage, (2016)SCALENet: A SCalable Low power AccELerator for Real-time Embedded Deep Neural Networks., , and . ACM Great Lakes Symposium on VLSI, page 129-134. ACM, (2018)LESS: Big data sketching and Encryption on low power platform., , , and . DATE, page 1631-1634. IEEE, (2017)Generating Deontic Obligations From Utility-Maximizing Systems., and . AIES, page 653-663. ACM, (2022)Formal Ethical Obligations in Reinforcement Learning Agents: Verification and Policy Updates., and . CoRR, (2024)