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Burak Aksar
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Counterfactual explanations for multivariate time series
E Ates, B Aksar, VJ Leung, AK Coskun
2021 international conference on applied artificial intelligence (ICAPAI), 1-8, 2021
742021
HPAS: An HPC performance anomaly suite for reproducing performance variations
E Ates, Y Zhang, B Aksar, J Brandt, VJ Leung, M Egele, AK Coskun
Proceedings of the 48th International Conference on Parallel Processing, 1-10, 2019
222019
Proctor: A semi-supervised performance anomaly diagnosis framework for production hpc systems
B Aksar, Y Zhang, E Ates, B Schwaller, O Aaziz, VJ Leung, J Brandt, ...
High Performance Computing: 36th International Conference, ISC High …, 2021
142021
E2EWatch: an end-to-end anomaly diagnosis framework for production HPC systems
B Aksar, B Schwaller, O Aaziz, VJ Leung, J Brandt, M Egele, AK Coskun
Euro-Par 2021: Parallel Processing: 27th International Conference on …, 2021
122021
From natural language to workflows: Towards emergent intelligence in robotic process automation
T Chakraborti, Y Rizk, V Isahagian, B Aksar, F Fuggitti
International Conference on Business Process Management, 123-137, 2022
102022
Albadross: Active learning based anomaly diagnosis for production hpc systems
B Aksar, E Sencan, B Schwaller, O Aaziz, VJ Leung, J Brandt, B Kulis, ...
2022 IEEE International Conference on Cluster Computing (CLUSTER), 369-380, 2022
52022
Explainable Machine Learning Frameworks for Managing HPC Systems.
E Ates, B Aksar, VJ Leung, AK Coskun
Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2020
22020
AD for Machine Learning Approach to Understanding HPC Application Performance Variation Poster.
B Aksar, B Schwaller, OR Aaziz, E Ates, JM Brandt, A Coskun, M Egele, ...
Sandia National Lab.(SNL-NM), Albuquerque, NM (United States); Sandia …, 2019
22019
Runtime Performance Anomaly Diagnosis in Production HPC Systems Using Active Learning
B Aksar, E Sencan, B Schwaller, O Aaziz, VJ Leung, J Brandt, B Kulis, ...
IEEE Transactions on Parallel and Distributed Systems, 2024
12024
Prodigy: Towards unsupervised anomaly detection in production hpc systems
B Aksar, E Sencan, B Schwaller, O Aaziz, VJ Leung, J Brandt, B Kulis, ...
Proceedings of the International Conference for High Performance Computing …, 2023
12023
Towards Practical Machine Learning Frameworks for Performance Diagnostics in Supercomputers
B Aksar, E Sencan, B Schwaller, VJ Leung, J Brandt, B Kulis, M Egele, ...
Proceedings of the First Workshop on AI for Systems, 1-6, 2023
12023
Using Monitoring Data to Improve HPC Performance via Network-Data-Driven Allocation
Y Zhang, B Aksar, O Aaziz, B Schwaller, J Brandt, V Leung, M Egele, ...
2021 IEEE High Performance Extreme Computing Conference (HPEC), 1-7, 2021
12021
Comte: counterfactual explanations for supervised machine learning frameworks on multivariate time series data
VJ Leung, E Ates, B Aksar, AK Coskun
Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2021
12021
A Machine Learning Approach to Understanding HPC Application Performance Variation.
B Schwaller, B Aksar, OR Aaziz, E Ates, JM Brandt, A Coskun, M Egele, ...
Sandia National Lab.(SNL-NM), Albuquerque, NM (United States); Sandia …, 2019
12019
Machine learning-based performance analytics for high-performance computing systems
B Aksar
Boston University, 2024
2024
Explaining natural-language-to-flow pipelines
T Chakraborti, A Chaudhary, M Brachman, Q Pan, J Johnson, Y Rizk, ...
US Patent App. 17/804,627, 2023
2023
TESS: A Multi-intent Parser for Conversational Multi-Agent Systems with Decentralized Natural Language Understanding Models
B Aksar, Y Rizk, T Chakraborti
arXiv preprint arXiv:2312.11828, 2023
2023
Multi-agent chatbot with multi-intent recognition
B Aksar, Y Rizk, T Chakraborti
US Patent App. 17/662,484, 2023
2023
CoMTE: Counterfactual Explanations for Multivariate Time Series.
E Ates, B Aksar, AK Coskun, VJ Leung
Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2021
2021
Explainable Machine Learning Frameworks for Managing HPC Systems
B Aksar, E Ates, VJ Leung, AK Coskun
Workshop on Machine Learning for Computing Systems, Supercomputing'20, 2020
2020
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