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2020 – today
- 2025
[i1]Edi Muskardin, Tamim Burgstaller:
Passive Model Learning of Visibly Deterministic Context-free Grammars. CoRR abs/2508.16305 (2025)- 2024
- [j1]Mathias Uta, Alexander Felfernig, Viet-Man Le, Thi Ngoc Trang Tran, Damian Garber
, Sebastian Lubos, Tamim Burgstaller:
Knowledge-based recommender systems: overview and research directions. Frontiers Big Data 7 (2024) - [c6]Damian Garber, Alexander Felfernig, Viet-Man Le, Tamim Burgstaller, Merfat El Mansi:
An extensive comparison of preprocessing methods in the context of configuration space learning. ConfWS 2024: 81-90 - [c5]Edi Muskardin, Tamim Burgstaller, Martin Tappler, Bernhard K. Aichernig:
Active Model Learning of Git Version Control System. ICSTW 2024: 78-82 - [c4]Tamim Burgstaller, Damian Garber, Viet-Man Le, Alexander Felfernig:
Optimization Space Learning: A Lightweight, Noniterative Technique for Compiler Autotuning. SPLC (A) 2024: 36-46 - 2023
- [c3]Seda Polat Erdeniz, Michael Schrempf, Diether Kramer, Peter P. Rainer, Alexander Felfernig, Thi Ngoc Trang Tran, Tamim Burgstaller, Sebastian Lubos:
Computational Evaluation of Model-Agnostic Explainable AI Using Local Feature Importance in Healthcare. AIME 2023: 114-119 - [c2]Damian Garber, Tamim Burgstaller, Alexander Felfernig, Viet-Man Le, Sebastian Lubos, Trang Tran, Seda Polat Erdeniz:
Collaborative Recommendation of Search Heuristics For Constraint Solvers. ConfWS 2023: 38-44 - [c1]Seda Polat Erdeniz, Diether Kramer, Michael Schrempf, Peter P. Rainer, Alexander Felfernig, Thi Ngoc Trang Tran, Tamim Burgstaller, Sebastian Lubos:
Machine Learning Based Risk Prediction for Major Adverse Cardiovascular Events for ELGA-Authorized Clinics. dHealth 2023: 20-25
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