Publication list for members of
E194 - Institute of Information Systems Engineering
E194-06 Machine Learning
as authors or essentially involved persons
6 records (2020 - 2022)
Books and Book Editorships
T. Gärtner, A. Haywood, J. Redshaw, A. Taylor, A. Mason, J. Hirst (ed.):
"Machine Learning for Chemical Synthesis";
The Royal Society of Chemistry,
London,
2020,
ISBN: 978-1-78801-789-3;
25 pages.
Publications in Scientific Journals
A. Haywood, J. Redshaw, M. Hanson-Heine, A. Taylor, A. Brown, A. Mason, T. Gärtner, J. Hirst:
"Kernel Methods for Predicting Yields of Chemical Reactions";
Journal of Chemical Information and Modeling,
62
(2022),
9;
2077 pages.
Contributions to Proceedings
P. Indri, A. Bartoli, E. Medvet, L. Nenzi:
"One-Shot Learning of Ensembles of Temporal Logic Formulas for Anomaly Detection in Cyber-Physical Systems";
in: "EuroGP 2022: Proceedings of the 25th European Conference on Genetic Programming",
20-22 , April;
Springer-Verlag,
Madrid, Spain,
2022,
32
- 47.
A. Krauck, D. Penz, M. Schedl:
"Team JKU-AIWarriors in the ACM Recommender Systems Challenge 2021: Lightweight XGBoost Recommendation Approach Leveraging User Features";
in: "RecSysChallenge 2021: RecSysChallenge '21: Proceedings of the Recommender Systems Challenge 2021",
ACM,
2021,
39
- 43.
M. Schedl, S. Brandl, O. Lesota, E. Parada-Cabaleiro, D. Penz, N. Rekabsaz:
"LFM-2b: A Dataset of Enriched Music Listening Events for Recommender Systems Research and Fairness Analysis";
in: "CHIIR '22: ACM SIGIR Conference on Human Information Interaction and Retrieval",
ACM,
2022,
337
- 341.
M. Thiessen, T. Gärtner:
"Active Learning of Convex Halfspaces on Graphs";
in: "Advances in Neural Information Processing Systems 34",
Advances in Neural Information Processing Systems 34,
2021.
