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7SARDE: A Framework for Continuous and Self-Adaptive Resource Demand Estimation
J. Grohmann, S. Eismann, A. Bauer, S. Spinner, J. Blum, N. Herbst, и S. Kounev. ACM Transactions on Autonomous and Adaptive Systems, (июня 2021)
3 лет назад , @andre.bauer
myown
descartes
algorithms
resource
Self-adaptive
learning
demand
performance
self-tuning
estimation
systems
optimization
statistical_estimation_and_machine_learning
machine
prediction
t_journalmagazine
myowndescartesalgorithmsresourceSelf-adaptivelearningdemandperformanceself-tuningestimationsystemsoptimizationstatistical_estimation_and_machine_learningmachinepredictiont_journalmagazine
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7SARDE: A Framework for Continuous and Self-Adaptive Resource Demand Estimation
J. Grohmann, S. Eismann, A. Bauer, S. Spinner, J. Blum, N. Herbst, и S. Kounev. ACM Transactions on Autonomous and Adaptive Systems, (июня 2021)
3 лет назад , @samuel.kounev
myown
descartes
algorithms
resource
Self-adaptive
learning
demand
performance
self-tuning
estimation
systems
optimization
statistical_estimation_and_machine_learning
machine
prediction
t_journalmagazine
myowndescartesalgorithmsresourceSelf-adaptivelearningdemandperformanceself-tuningestimationsystemsoptimizationstatistical_estimation_and_machine_learningmachinepredictiont_journalmagazine
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7SARDE: A Framework for Continuous and Self-Adaptive Resource Demand Estimation
J. Grohmann, S. Eismann, A. Bauer, S. Spinner, J. Blum, N. Herbst, и S. Kounev. ACM Transactions on Autonomous and Adaptive Systems, (июня 2021)
3 лет назад , @simon.eismann
myown
descartes
algorithms
resource
Self-adaptive
learning
demand
performance
self-tuning
estimation
systems
optimization
statistical_estimation_and_machine_learning
machine
prediction
t_journalmagazine
myowndescartesalgorithmsresourceSelf-adaptivelearningdemandperformanceself-tuningestimationsystemsoptimizationstatistical_estimation_and_machine_learningmachinepredictiont_journalmagazine
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7SARDE: A Framework for Continuous and Self-Adaptive Resource Demand Estimation
J. Grohmann, S. Eismann, A. Bauer, S. Spinner, J. Blum, N. Herbst, и S. Kounev. ACM Transactions on Autonomous and Adaptive Systems, (июня 2021)
3 лет назад , @nikolas.herbst
myown
descartes
algorithms
resource
Self-adaptive
learning
demand
performance
self-tuning
estimation
systems
optimization
statistical_estimation_and_machine_learning
machine
prediction
t_journalmagazine
myowndescartesalgorithmsresourceSelf-adaptivelearningdemandperformanceself-tuningestimationsystemsoptimizationstatistical_estimation_and_machine_learningmachinepredictiont_journalmagazine
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7SARDE: A Framework for Continuous and Self-Adaptive Resource Demand Estimation
J. Grohmann, S. Eismann, A. Bauer, S. Spinner, J. Blum, N. Herbst, и S. Kounev. ACM Transactions on Autonomous and Adaptive Systems, (июня 2021)
3 лет назад , @joh.grohmann
myown
select
descartes
algorithms
resource
Self-adaptive
learning
demand
performance
self-tuning
estimation
systems
optimization
statistical_estimation_and_machine_learning
machine
prediction
t_journalmagazine
myownselectdescartesalgorithmsresourceSelf-adaptivelearningdemandperformanceself-tuningestimationsystemsoptimizationstatistical_estimation_and_machine_learningmachinepredictiont_journalmagazine
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8SuanMing: Explainable Prediction of Performance Degradations in Microservice Applications
J. Grohmann, M. Straesser, A. Chalbani, S. Eismann, Y. Arian, N. Herbst, N. Peretz, и S. Kounev. Proceedings of the 12th ACM/SPEC International Conference on Performance Engineering (ICPE), New York, NY, USA, ACM, (апреля 2021)Acceptance Rate: 29%.
4 лет назад , @martinstraesser
myown
t_full
descartes
statistical_estimation_and_machine_learning
prediction
performance
myownt_fulldescartesstatistical_estimation_and_machine_learningpredictionperformance
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8SuanMing: Explainable Prediction of Performance Degradations in Microservice Applications
J. Grohmann, M. Straesser, A. Chalbani, S. Eismann, Y. Arian, N. Herbst, N. Peretz, и S. Kounev. Proceedings of the 12th ACM/SPEC International Conference on Performance Engineering (ICPE), New York, NY, USA, ACM, (апреля 2021)Acceptance Rate: 29%.
4 лет назад , @samuel.kounev
myown
t_full
descartes
statistical_estimation_and_machine_learning
prediction
performance
myownt_fulldescartesstatistical_estimation_and_machine_learningpredictionperformance
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8SuanMing: Explainable Prediction of Performance Degradations in Microservice Applications
J. Grohmann, M. Straesser, A. Chalbani, S. Eismann, Y. Arian, N. Herbst, N. Peretz, и S. Kounev. Proceedings of the 12th ACM/SPEC International Conference on Performance Engineering (ICPE), New York, NY, USA, ACM, (апреля 2021)Acceptance Rate: 29%.
4 лет назад , @simon.eismann
myown
t_full
descartes
statistical_estimation_and_machine_learning
prediction
performance
myownt_fulldescartesstatistical_estimation_and_machine_learningpredictionperformance
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8SuanMing: Explainable Prediction of Performance Degradations in Microservice Applications
J. Grohmann, M. Straesser, A. Chalbani, S. Eismann, Y. Arian, N. Herbst, N. Peretz, и S. Kounev. Proceedings of the 12th ACM/SPEC International Conference on Performance Engineering (ICPE), New York, NY, USA, ACM, (апреля 2021)Acceptance Rate: 29%.
4 лет назад , @nikolas.herbst
myown
t_full
descartes
statistical_estimation_and_machine_learning
prediction
performance
myownt_fulldescartesstatistical_estimation_and_machine_learningpredictionperformance
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8SuanMing: Explainable Prediction of Performance Degradations in Microservice Applications
J. Grohmann, M. Straesser, A. Chalbani, S. Eismann, Y. Arian, N. Herbst, N. Peretz, и S. Kounev. Proceedings of the 12th ACM/SPEC International Conference on Performance Engineering (ICPE), New York, NY, USA, ACM, (апреля 2021)Acceptance Rate: 29%.
4 лет назад , @joh.grohmann
myown
select
t_full
descartes
statistical_estimation_and_machine_learning
prediction
performance
myownselectt_fulldescartesstatistical_estimation_and_machine_learningpredictionperformance
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5Baloo: Measuring and Modeling the Performance Configurations of Distributed DBMS
J. Grohmann, D. Seybold, S. Eismann, M. Leznik, S. Kounev, и J. Domaschka. 2020 28th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS), стр. 1--8. IEEE, (ноября 2020)Acceptance Rate: 27%.
4 лет назад , @samuel.kounev
myown
t_full
performance_modeling
descartes
statistical_estimation_and_machine_learning
prediction
performance
automated_model_learning
myownt_fullperformance_modelingdescartesstatistical_estimation_and_machine_learningpredictionperformanceautomated_model_learning
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5Baloo: Measuring and Modeling the Performance Configurations of Distributed DBMS
J. Grohmann, D. Seybold, S. Eismann, M. Leznik, S. Kounev, и J. Domaschka. 2020 28th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS), стр. 1--8. IEEE, (ноября 2020)Acceptance Rate: 27%.
4 лет назад , @simon.eismann
myown
t_full
performance_modeling
descartes
statistical_estimation_and_machine_learning
prediction
performance
automated_model_learning
myownt_fullperformance_modelingdescartesstatistical_estimation_and_machine_learningpredictionperformanceautomated_model_learning
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5Baloo: Measuring and Modeling the Performance Configurations of Distributed DBMS
J. Grohmann, D. Seybold, S. Eismann, M. Leznik, S. Kounev, и J. Domaschka. 2020 28th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS), стр. 1--8. IEEE, (ноября 2020)Acceptance Rate: 27%.
4 лет назад , @se-group
myown
t_full
performance_modeling
descartes
statistical_estimation_and_machine_learning
prediction
performance
automated_model_learning
myownt_fullperformance_modelingdescartesstatistical_estimation_and_machine_learningpredictionperformanceautomated_model_learning
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5Baloo: Measuring and Modeling the Performance Configurations of Distributed DBMS
J. Grohmann, D. Seybold, S. Eismann, M. Leznik, S. Kounev, и J. Domaschka. 2020 28th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS), стр. 1--8. IEEE, (ноября 2020)Acceptance Rate: 27%.
4 лет назад , @joh.grohmann
myown
select
t_full
performance_modeling
descartes
statistical_estimation_and_machine_learning
prediction
performance
automated_model_learning
myownselectt_fullperformance_modelingdescartesstatistical_estimation_and_machine_learningpredictionperformanceautomated_model_learning
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2Solving Explicit Dependencies for Architectural Performance Models
S. Eismann. University of Würzburg, Am Hubland, Informatikgebäude, 97074 Würzburg, Germany, Master Thesis, (марта 2017)<b>ASQF Award</b>.
5 лет назад , @simon.eismann
Thesis_supervised_by_SE_member
myown
se2_mastersthesis
DML
Performance
Design_of_software_and_systems
Analytical_and_simulation-based_analysis
descartes
Prediction
PRISMA
Meta-models
Thesis_supervised_by_Juergen_Walter
Thesis_supervised_by_SE_membermyownse2_mastersthesisDMLPerformanceDesign_of_software_and_systemsAnalytical_and_simulation-based_analysisdescartesPredictionPRISMAMeta-modelsThesis_supervised_by_Juergen_Walter
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6On Learning Parametric Dependencies from Monitoring Data
J. Grohmann, S. Eismann, и S. Kounev. Proceedings of the 10th Symposium on Software Performance 2019 (SSP'19), (ноября 2019)
5 лет назад , @simon.eismann
Statistical_estimation_and_machine_learning
myown
Performance
descartes
Self-aware-computing
Prediction
Automated_model_learning
Self-adaptive-systems
t_workshop
Statistical_estimation_and_machine_learningmyownPerformancedescartesSelf-aware-computingPredictionAutomated_model_learningSelf-adaptive-systemst_workshop
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6On Learning Parametric Dependencies from Monitoring Data
J. Grohmann, S. Eismann, и S. Kounev. Proceedings of the 10th Symposium on Software Performance 2019 (SSP'19), (ноября 2019)
5 лет назад , @samuel.kounev
Statistical_estimation_and_machine_learning
myown
Performance
descartes
Self-aware-computing
Prediction
Automated_model_learning
Self-adaptive-systems
t_workshop
Statistical_estimation_and_machine_learningmyownPerformancedescartesSelf-aware-computingPredictionAutomated_model_learningSelf-adaptive-systemst_workshop
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5Detecting Parametric Dependencies for Performance Models Using Feature Selection Techniques
J. Grohmann, S. Eismann, S. Elflein, M. Mazkatli, J. von Kistowski, и S. Kounev. 2019 IEEE 27th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS), стр. 309--322. IEEE Computer Society, (октября 2019)Acceptance Rate: 23.8% (29/122).
5 лет назад , @samuel.kounev
Statistical_estimation_and_machine_learning
myown
DML
Performance
t_full
descartes
Self-aware-computing
Prediction
PRISMA
Automated_model_learning
Statistical_estimation_and_machine_learningmyownDMLPerformancet_fulldescartesSelf-aware-computingPredictionPRISMAAutomated_model_learning
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5Detecting Parametric Dependencies for Performance Models Using Feature Selection Techniques
J. Grohmann, S. Eismann, S. Elflein, M. Mazkatli, J. von Kistowski, и S. Kounev. 2019 IEEE 27th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS), стр. 309--322. IEEE Computer Society, (октября 2019)Acceptance Rate: 23.8% (29/122).
5 лет назад , @simon.eismann
Statistical_estimation_and_machine_learning
myown
DML
Performance
t_full
descartes
Self-aware-computing
Prediction
PRISMA
Automated_model_learning
Statistical_estimation_and_machine_learningmyownDMLPerformancet_fulldescartesSelf-aware-computingPredictionPRISMAAutomated_model_learning
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5Integrating Statistical Response Time Models in Architectural Performance Models
S. Eismann, J. Grohmann, J. Walter, J. von Kistowski, и S. Kounev. Proceedings of the 2019 IEEE International Conference on Software Architecture (ICSA), стр. 71--80. IEEE, (марта 2019)Acceptance Rate: 21,9\% (21/96).
5 лет назад , @joh.grohmann
Statistical_estimation_and_machine_learning
myown
DML
Performance
t_full
Analytical_and_simulation-based_analysis
descartes
Prediction
Formal_architecture_modeling
Meta-models
QPN
QPME
Simulation
PRISMA
Statistical_estimation_and_machine_learningmyownDMLPerformancet_fullAnalytical_and_simulation-based_analysisdescartesPredictionFormal_architecture_modelingMeta-modelsQPNQPMESimulationPRISMA
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публикации (спрятать)57
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7SARDE: A Framework for Continuous and Self-Adaptive Resource Demand Estimation

7SARDE: A Framework for Continuous and Self-Adaptive Resource Demand Estimation

7SARDE: A Framework for Continuous and Self-Adaptive Resource Demand Estimation

7SARDE: A Framework for Continuous and Self-Adaptive Resource Demand Estimation

7SARDE: A Framework for Continuous and Self-Adaptive Resource Demand Estimation

8SuanMing: Explainable Prediction of Performance Degradations in Microservice Applications

8SuanMing: Explainable Prediction of Performance Degradations in Microservice Applications

8SuanMing: Explainable Prediction of Performance Degradations in Microservice Applications

8SuanMing: Explainable Prediction of Performance Degradations in Microservice Applications

8SuanMing: Explainable Prediction of Performance Degradations in Microservice Applications

5Baloo: Measuring and Modeling the Performance Configurations of Distributed DBMS

5Baloo: Measuring and Modeling the Performance Configurations of Distributed DBMS

5Baloo: Measuring and Modeling the Performance Configurations of Distributed DBMS

5Baloo: Measuring and Modeling the Performance Configurations of Distributed DBMS

2Solving Explicit Dependencies for Architectural Performance Models

6On Learning Parametric Dependencies from Monitoring Data

6On Learning Parametric Dependencies from Monitoring Data

5Detecting Parametric Dependencies for Performance Models Using Feature Selection Techniques

5Detecting Parametric Dependencies for Performance Models Using Feature Selection Techniques

5Integrating Statistical Response Time Models in Architectural Performance Models

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