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Transfer learning for performance modeling of configurable systems: an exploratory analysis.

, , , , , and . ASE, page 497-508. IEEE Computer Society, (2017)

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Understanding similarities and differences in software development practices across domains., , , , and . ICGSE, page 74-84. IEEE / ACM, (2019)Ensemble-Based Software Engineering for Modern Computing Platforms., , , , , , , and . ACM SIGSOFT Softw. Eng. Notes, 45 (1): 28-30 (2020)Reconciling High Accuracy, Cost-Efficiency, and Low Latency of Inference Serving Systems., , , , , , , and . EuroMLSys@EuroSys, page 78-86. ACM, (2023)ConfigCrusher: White-Box Performance Analysis for Configurable Systems., , , , , and . CoRR, (2019)Transfer Learning for Performance Modeling of Deep Neural Network Systems., , and . OpML, page 43-46. USENIX Association, (2019)FlexiBO: A Decoupled Cost-Aware Multi-objective Optimization Approach for Deep Neural Networks (Abstract Reprint)., , , and . AAAI, page 22700. AAAI Press, (2024)Change Point Detection for MongoDB Time Series Performance Regression., , , , , and . ICPE (Companion), page 45-48. ACM, (2022)Modelling multi-tier enterprise applications behaviour with design of experiments technique., and . QUDOS@SIGSOFT FSE, page 13-18. ACM, (2015)A metric for measuring the degree of entity-centric service cohesion., , , , and . SOCA, page 1-5. IEEE Computer Society, (2010)Kuksa: A Cloud-Native Architecture for Enabling Continuous Delivery in the Automotive Domain., , , and . PROFES, volume 11915 of Lecture Notes in Computer Science, page 455-472. Springer, (2019)