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Jasmin Bogatinovski
Jasmin Bogatinovski
AI Researcher
Geverifieerd e-mailadres voor tu-berlin.de - Homepage
Titel
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Self-attentive classification-based anomaly detection in unstructured logs
S Nedelkoski, J Bogatinovski, A Acker, J Cardoso, O Kao
2020 IEEE International Conference on Data Mining (ICDM), 1196-1201, 2020
1752020
Comprehensive comparative study of multi-label classification methods
J Bogatinovski, L Todorovski, S Džeroski, D Kocev
Expert Systems with Applications 203, 117215, 2022
1412022
Self-supervised log parsing
J Bogatinovski, S Nedelkoski, A Acker, J Cardoso, O Kao
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2020
91*2020
Microdiag: Fine-grained performance diagnosis for microservice systems
L Wu, J Tordsson, J Bogatinovski, E Elmroth, O Kao
2021 IEEE/ACM International Workshop on Cloud Intelligence …, 2021
642021
Performance diagnosis in cloud microservices using deep learning
L Wu, J Bogatinovski, S Nedelkoski, J Tordsson, O Kao
International Conference on Service-Oriented Computing, 85-96, 2020
542020
Multi-source distributed system data for ai-powered analytics
S Nedelkoski, J Bogatinovski, AK Mandapati, S Becker, J Cardoso, O Kao
Service-Oriented and Cloud Computing: 8th IFIP WG 2.14 European Conference …, 2020
482020
Self-supervised anomaly detection from distributed traces
J Bogatinovski, S Nedelkoski, J Cardoso, O Kao
2020 IEEE/ACM 13th International Conference on Utility and Cloud Computing …, 2020
442020
Robust and Transferable Anomaly Detection in Log Data using Pre-Trained Language Models
J Bogatinovski, H Ott, A Acker, S Nedelkoski, O Kao
2021 IEEE/ACM International Workshop on Cloud Intelligence …, 2021
332021
A2log: attentive augmented log anomaly detection
T Wittkopp, A Acker, S Nedelkoski, J Bogatinovski, D Scheinert, W Fan, ...
arXiv preprint arXiv:2109.09537, 2021
322021
Multi-source anomaly detection in distributed it systems
J Bogatinovski, S Nedelkoski
International Conference on Service-Oriented Computing, 201-213, 2020
202020
Artificial intelligence for it operations (aiops) workshop white paper
J Bogatinovski, S Nedelkoski, A Acker, F Schmidt, T Wittkopp, S Becker, ...
arXiv preprint arXiv:2101.06054, 2021
182021
Less is more: Selecting the right benchmarking set of data for time series classification
T Eftimov, G Petelin, G Cenikj, A Kostovska, G Ispirova, P Korošec, ...
Expert Systems with Applications, 10.1016/j.eswa.2022.116871, 2022
102022
Leveraging log instructions in log-based anomaly detection
J Bogatinovski, G Madjarov, S Nedelkoski, J Cardoso, O Kao
2022 IEEE International Conference on Services Computing (SCC), 321-326, 2022
92022
Failure identification from unstable log data using deep learning
J Bogatinovski, S Nedelkoski, L Wu, J Cardoso, O Kao
2022 22nd IEEE International Symposium on Cluster, Cloud and Internet …, 2022
92022
Explaining the performance of multilabel classification methods with data set properties
J Bogatinovski, L Todorovski, S Džeroski, D Kocev
International Journal of Intelligent Systems, 10.1002/int.22835, 2022
82022
Feature extraction for heartbeat classification in single-lead ECG
J Bogatinovski, D Kocev, A Rashkovska
2019 42nd International Convention on Information and Communication …, 2019
72019
Qulog: Data-driven approach for log instruction quality assessment
J Bogatinovski, S Nedelkoski, A Acker, J Cardoso, O Kao
Proceedings of the 30th IEEE/ACM International Conference on Program …, 2022
62022
A catalogue with semantic annotations makes multilabel datasets FAIR
J Bogatinovski, A Kostovska, S Džeroski, D Kocev, P Panov
Scientific Reports 12 (1), 1-11, 2022
6*2022
Auto-logging: AI-centred logging instrumentation
J Bogatinovski, O Kao
2023 IEEE/ACM 45th International Conference on Software Engineering: New …, 2023
52023
First ce matters: On the importance of long term properties on memory failure prediction
J Bogatinovski, O Kao, Q Yu, J Cardoso
2022 IEEE International Conference on Big Data (Big Data), 4733-4736, 2022
42022
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Artikelen 1–20