39 citations · 42 across the 4 of their papers we have counts for
4 papers
e-Fold Cross-Validation for Recommender-System Evaluation
Moritz Baumgart, Lukas Wegmeth, Tobias Vente +1
To combat the rising energy consumption of recommender systems we implement a novel alternative for k-fold cross validation. This alternative, named e-fold cross validation, aims t…
From Clicks to Carbon: The Environmental Toll of Recommender Systems
Tobias Vente, Lukas Wegmeth, Alan Said +1
As global warming soars, the need to assess the environmental impact of research is becoming increasingly urgent. Despite this, few recommender systems research papers address thei…
Revealing the Hidden Impact of Top-N Metrics on Optimization in Recommender Systems
Lukas Wegmeth, Tobias Vente, Lennart Purucker
The hyperparameters of recommender systems for top-n predictions are typically optimized to enhance the predictive performance of algorithms. Thereby, the optimization algorithm, e…
The Impact of Feature Quantity on Recommendation Algorithm Performance: A Movielens-100K Case Study
Lukas Wegmeth
Recent model-based Recommender Systems (RecSys) algorithms emphasize on the use of features, also called side information, in their design similar to algorithms in Machine Learning…