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Energy-Efficient Adaptive Machine Learning on IoT End-Nodes With Class-Dependent Confidence.

, , , , , and . ICECS, page 1-4. IEEE, (2020)

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Synthesis of application-specific memories for power optimization in embedded systems., , , and . DAC, page 300-303. ACM, (2000)Computational Kernels and their Application to Sequential Power Optimization., , , , , and . DAC, page 764-769. ACM Press, (1998)Algorithms for Approximate FSM Traversal., , , , and . DAC, page 25-30. ACM Press, (1993)Architectural Leakage Power Minimization of Scratchpad Memories by Application-Driven Subbanking., , , and . IEEE Trans. Computers, 59 (7): 891-904 (2010)Exploration of different implementation styles for graphene-based reconfigurable gates., , , and . ICICDT, page 21-24. IEEE, (2013)PVInGrid: A Distributed Infrastructure for Evaluating the Integration of Photovoltaic Systems in Smart Grid., , , , , and . DoCEIS, volume 499 of IFIP Advances in Information and Communication Technology, page 316-324. (2017)Regression-based RTL power models for controllers., , , , and . ACM Great Lakes Symposium on VLSI, page 147-152. ACM, (2000)Combining wire swapping and spacing for low-power deep-submicron buses., , and . ACM Great Lakes Symposium on VLSI, page 198-202. ACM, (2003)Clock-tree power optimization based on RTL clock-gating., , , and . DAC, page 622-627. ACM, (2003)Statistical Battery Models and Variation-Aware Battery Management., , and . DAC, page 135:1-135:6. ACM, (2014)