Publications

Google Scholar, ResearchGate

Conferences

1. Revealing the Hidden Impact of Top-N Metrics on Optimization in Recommender Systems. L. Wegmeth, T. Vente, L. Purucker. ECIR (Full Paper). [ArXiv, code]

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

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

Workshops, Tutorials, Demos & Others

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

2. 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]

3. 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]