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2020 – today
- 2025
[c12]Keerthiga Rajenthiram, Milad Abdullah, Ilias Gerostathopoulos
, Petr Hnetynka, Tomás Bures, Gerard Pons, Besim Bilalli, Anna Queralt:
Towards Continuous Experiment-Driven MLOps. CAIN 2025: 89-94- [c11]Milad Abdullah, Petr Hnetynka, Jiyan Salim Mahmud:
Temporal Harmonization of Heterogeneous Software Logs: A Unified Model for Time-Series Analysis. ECSA (Tracks and Workshops) 2025: 345-353 - [c10]Petr Hnetynka, Tomás Bures, Ilias Gerostathopoulos, Milad Abdullah, Keerthiga Rajenthiram:
A Model-Based Approach to Experiment-Driven Evolution of ML Workflows. MODELSWARD 2025: 354-362 - [c9]Milad Abdullah, David Georg Reichelt, Vojtech Horký, Lubomír Bulej, Tomás Bures, Petr Tuma:
A Combined Approach to Performance Regression Testing Resource Usage Reduction. PROMISE 2025: 75-84 - [i2]Keerthiga Rajenthiram, Milad Abdullah, Ilias Gerostathopoulos, Petr Hnetynka, Tomás Bures, Gerard Pons, Besim Bilalli, Anna Queralt:
Towards Continuous Experiment-driven MLOps. CoRR abs/2503.03455 (2025) - 2024
- [c8]Keerthiga Rajenthiram, Milad Abdullah, Ilias Gerostathopoulos, Petr Hnetynka, Tomás Bures:
ExpEngine: A Tool for Data Analytics Workflow Optimization Through User-Driven Experimentation. ACSOS-C 2024: 182-183 - [c7]Milad Abdullah, Michal Töpfer, Tomás Bures:
Robin: A Systematic Literature Mapping Management Tool. SEAA 2024: 284-287 - 2023
- [j1]Michal Töpfer, Milad Abdullah, Tomás Bures, Petr Hnetynka, Martin Krulis:
Machine-learning abstractions for component-based self-optimizing systems. Int. J. Softw. Tools Technol. Transf. 25(5): 717-731 (2023) - [c6]Milad Abdullah, Lubomír Bulej, Tomás Bures, Vojtech Horký, Petr Tuma:
Early Stopping of Non-productive Performance Testing Experiments Using Measurement Mutations. SEAA 2023: 86-93 - [i1]Michal Töpfer, Milad Abdullah, Tomás Bures, Petr Hnetynka, Martin Krulis:
Ensemble-based modeling abstractions for modern self-optimizing systems. CoRR abs/2309.05823 (2023) - 2022
- [c5]Michal Töpfer, Milad Abdullah, Martin Krulis, Tomás Bures, Petr Hnetynka:
ML-DEECo: a Machine-Learning-Enabled Framework for Self-organizing Components. ACSOS-C 2022: 66-69 - [c4]Milad Abdullah:
Controlling Automatic Experiment-Driven Systems Using Statistics and Machine Learning. ECSA (Tracks and Workshops) 2022: 105-119 - [c3]Milad Abdullah, Michal Töpfer, Tomás Bures, Petr Hnetynka, Martin Krulis, Frantisek Plásil:
Introducing Estimators - Abstraction for Easy ML Employment in Self-adaptive Architectures. ECSA (Tracks and Workshops) 2022: 370-385 - [c2]Milad Abdullah, Lubomír Bulej, Tomás Bures, Petr Hnetynka, Vojtech Horký, Petr Tuma:
Reducing Experiment Costs in Automated Software Performance Regression Detection. SEAA 2022: 56-59 - [c1]Michal Töpfer, Milad Abdullah, Tomás Bures, Petr Hnetynka, Martin Krulis:
Ensemble-Based Modeling Abstractions for Modern Self-optimizing Systems. ISoLA (3) 2022: 318-334
Coauthor Index
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