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Shadow Kernels: A General Mechanism For Kernel Specialization in Existing Operating Systems., , , , and . ACM SIGOPS Oper. Syst. Rev., 50 (1): 3-8 (2016)Provenance-based computing.. University of Cambridge, UK, (2019)British Library, EThOS.Non-repudiable disk I/O in untrusted kernels., , , , and . APSys, page 24:1-24:6. ACM, (2017)Accelerating the Configuration Tuning of Big Data Analytics with Similarity-aware Multitask Bayesian Optimization., , , and . IEEE BigData, page 266-275. IEEE, (2020)To Tune or Not to Tune?: In Search of Optimal Configurations for Data Analytics., , , , and . KDD, page 2494-2504. ACM, (2020)Improving the visualization of electron-microscopy data through optical flow interpolation., , , and . SCC, page 103-110. ACM, (2011)ProvMark: A Provenance Expressiveness Benchmarking System., , , , , , , and . Middleware, page 268-279. ACM, (2019)Structural Analysis of Whole-System Provenance Graphs., , , , , and . IPAW, volume 11017 of Lecture Notes in Computer Science, page 241-244. Springer, (2018)Resourceful: Monitoring under the Microscope., , and . login Usenix Mag., (2017)Tuneful: An Online Significance-Aware Configuration Tuner for Big Data Analytics., , , , and . CoRR, (2020)