Publications

Google Scholar, ResearchGate

Conferences

1. Automated Learning of Software Configuration Spaces is not Easy
   M. Weiß, R. Müller, L. Güthing, T. Vente, L. Wegmeth, I. Schaefer, M. Lochau. ACM SPLC’25 (Full Paper)

2. Checky, the Paper-Submission Checklist Generator for Authors, Reviewers and LLMs
   J. Beel, B. Gipp, D. Jannach, A. Said, L. Wegmeth, T Vente. ECIR’25 (Demo Paper)
   [ACM Digital Library, PDF, code]

3. From Clicks to Carbon: The Environmental Toll of Recommender Systems
   T. Vente, L. Wegmeth, A. Said, J. Beel. ACM RecSys’24 (Full Paper, Reproducibility Track)
   [ACM Digital Library, PDF, code, ACM RecSys’25 presentation]

4. Recommender Systems Algorithm Selection for Ranking Prediction on Implicit Feedback Datasets
   L. Wegmeth, T. Vente, J. Beel. ACM RecSys’24 (LBR PAPER)
   [ACM Digital Library, PDF, code]

5. Revealing the Hidden Impact of Top-N Metrics on Optimization in Recommender Systems
   L. Wegmeth, T. Vente, L. Purucker. ECIR’24 (Full Paper)
   [ACM Digital Library, PDF, code]

6. From Theory to Practice: Implementing and Evaluating e-Fold Cross-Validation
   C. Mahlich, T. Vente, J. Beel CAIMLR’24 (Full Paper)
   [SPIE Digital Library, PDF, code]

7. Introducing LensKit-Auto, an Experimental Automated Recommender System (AutoRecSys) Toolkit
   T. Vente, M.D. Ekstrand, J. Beel. RecSys’23 (Demo Track)
   [ACM Digital Library, PDF, code, video]

8. Advancing Automation of Design Decisions in Recommender System Pipelines
   T. Vente. RecSys’23 (Doctoral Symposium)
   [ACM Digital Library]

Workshops, Tutorials, Demos & Others

1. The Potential of AutoML for Recommender Systems
   T. Vente, L. Wegmeth, J. Beel. HyPer Workshop @ ACM UMAP’25 (Full Paper)
   [ACM Digital Library, code]

2. Greedy Ensemble Selection for Top-N Recommendations
   T. Vente, Z. Mehta, L. Wegmeth, J. Beel. RobustRecSys Workshop @ RecSys’24 (Full Paper)
   [CEUR Workshop Proceedings, PDF, code]

3. Removing Bad Influence: Identifying and Pruning Detrimental Users in Collaborative Filtering Recommender Systems
   P. Meister, L. Wegmeth, T. Vente, J. Beel. RobustRecSys Workshop @ RecSys’24 (Short Paper)
   [CEUR Workshop Proceedings, PDF, code]

4. EMERS: Energy Meter for Recommender Systems
   L. Wegmeth, T. Vente, A. Said, J. Beel. RecSoGood Workshop @ RecSys’24 (Short Paper)
   [Springer, PDF, code, video]

5. e-Fold Cross-Validation for Recommender-System Evaluation
   M. Baumgart, L. Wegmeth, T. Vente, J. Beel. RecSoGood Workshop @ RecSys’24 (Short Paper)
   [Springer, PDF]

6. Sustainable Recommender Systems: Optimizing Dataset Size for Energy-Efficient Algorithm Performance
   A. Arabzadeh, T. Vente, J. Beel. RecSoGood Workshop @ RecSys’24 (Short Paper)
   [Springer, PDF, code]

7. The Effect of Random Seeds for Data Splitting on Recommendation Accuracy
   L. Wegmeth, T. Vente, L. Purucker, J. Beel. PERSPECTIVES ‘23 (RecSys Workshop)
   [CEUR Workshop Proceedings, PDF, code, video]

8. The Challenges of Algorithm Selection and Hyperparameter Optimization for Recommender Systems
   L. Wegmeth, T. Vente, J.Beel COSEAL’23 (COnfiguration and SElection of ALgorithms Workshop)
   [poster]

9. The Feasibility of Greedy Ensemble Selection for Automated Recommender Systems
   T. Vente, L. Purucker, J. Beel. COSEAL’22 (COnfiguration and SElection of ALgorithms Workshop)
   [poster]