Computational Evaluation of Model-Agnostic Explainable AI Using Local Feature Importance in Healthcare. - Seda Polat Erdeniz; Michael Schrempf; Diether Kramer; Peter P. Rainer; Alexander Felfernig; Thi Ngoc Trang Tran; Tamim Burgstaller; Sebastian Lubos (AIME, 2023)

Collaborative Recommendation of Search Heuristics For Constraint Solvers. - Damian Garber; Tamim Burgstaller; Alexander Felfernig; Viet-Man Le; Sebastian Lubos; Trang Tran 002; Seda Polat Erdeniz (ConfWS, 2023)

Machine Learning Based Risk Prediction for Major Adverse Cardiovascular Events for ELGA-Authorized Clinics. - Seda Polat Erdeniz; Diether Kramer; Michael Schrempf; Peter P. Rainer; Alexander Felfernig; Thi Ngoc Trang Tran; Tamim Burgstaller; Sebastian Lubos (dHealth, 2023)

An extensive comparison of preprocessing methods in the context of configuration space learning. - Damian Garber; Alexander Felfernig; Viet-Man Le; Tamim Burgstaller; Merfat El Mansi (ConfWS, 2024)

Active Model Learning of Git Version Control System. - Edi Muskardin; Tamim Burgstaller; Martin Tappler; Bernhard K. Aichernig (ICSTW, 2024)

Optimization Space Learning: A Lightweight, Noniterative Technique for Compiler Autotuning. - Tamim Burgstaller; Damian Garber; Viet-Man Le; Alexander Felfernig (SPLC (A), 2024)

Knowledge-based recommender systems: overview and research directions. - Mathias Uta; Alexander Felfernig; Viet-Man Le; Thi Ngoc Trang Tran; Damian Garber; Sebastian Lubos; Tamim Burgstaller (Frontiers Big Data, 2024)