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CoPPer: Soft Real-Time Application Performance Using Hardware Power Capping., , , and . ICAC, page 31-41. IEEE, (2019)Embodied Self-Aware Computing Systems., , and . Proc. IEEE, 108 (7): 1027-1046 (2020)Automatic and Efficient Customization of Neural Networks for ML Applications., , , , , , and . CoRR, (2023)ALERT: Accurate Learning for Energy and Timeliness., , , , , and . USENIX ATC, page 353-369. USENIX Association, (2020)ChameleonAPI: Automatic and Efficient Customization of Neural Networks for ML Applications., , , , , , and . OSDI, page 365-386. USENIX Association, (2024)SeeSAw: Optimizing Performance of In-Situ Analytics Applications under Power Constraints., , and . IPDPS, page 789-798. IEEE, (2020)AgileCtrl: a self-adaptive framework for configuration tuning., , and . ESEC/SIGSOFT FSE, page 459-471. ACM, (2022)Generalizable and interpretable learning for configuration extrapolation., , , and . ESEC/SIGSOFT FSE, page 728-740. ACM, (2021)Budget RNNs: Multi-Capacity Neural Networks to Improve In-Sensor Inference Under Energy Budgets., and . RTAS, page 143-156. IEEE, (2021)Introduction of a Pathophysiology-Based Diagnostic Decision Support System and Its Potential Impact on the Use of AI in Healthcare., , , , , and . MedInfo, volume 264 of Studies in Health Technology and Informatics, page 1696-1697. IOS Press, (2019)