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Lukas Wegmeth
Lukas Wegmeth
在 uni-siegen.de 的电子邮件经过验证 - 首页
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A machine learning framework for automated accident detection based on multimodal sensors in cars
H Hozhabr Pour, F Li, L Wegmeth, C Trense, R Doniec, M Grzegorzek, ...
Sensors 22 (10), 3634, 2022
502022
From Clicks to Carbon: The Environmental Toll of Recommender Systems
T Vente, L Wegmeth, A Said, J Beel
Proceedings of the 18th ACM Conference on Recommender Systems, 2024
122024
The Effect of Random Seeds for Data Splitting on Recommendation Accuracy
L Wegmeth, T Vente, L Purucker, J Beel
Proceedings of the 3rd Perspectives on the Evaluation of Recommender Systems …, 2023
122023
Feature extraction and classification of sensor signals in cars based on a modified codebook approach
H Hozhabr Pour, L Wegmeth, A Kordes, M Grzegorzek, R Wismüller
Progress in Computer Recognition Systems 11, 184-194, 2020
72020
EMERS: Energy Meter for Recommender Systems
L Wegmeth, T Vente, A Said, J Beel
RecSoGood: First International Workshop on Recommender Systems for …, 2024
52024
CaMeLS: Cooperative Meta-Learning Service for Recommender Systems
L Wegmeth, J Beel
Proceedings of the 2nd Perspectives on the Evaluation of Recommender Systems …, 2022
42022
Detecting Handwritten Mathematical Terms with Sensor Based Data
L Wegmeth, A Hoelzemann, K Van Laerhoven
arXiv preprint arXiv:2109.05594, 2021
42021
e-Fold Cross-Validation for Recommender-System Evaluation
M Baumgart, L Wegmeth, T Vente, J Beel
RecSoGood: First International Workshop on Recommender Systems for …, 2024
32024
Best-Practices for Offline Evaluations of Recommender Systems
J Beel, D Jannach, A Said, G Shani, T Vente, L Wegmeth
Dagstuhl Seminar Report, 2024
22024
The Impact of Feature Quantity on Recommendation Algorithm Performance: A Movielens-100K Case Study
L Wegmeth
arXiv preprint arXiv:2207.08713, 2022
22022
Informed Dataset-Selection with Algorithm Performance Spaces
J Beel, L Wegmeth, L Michiels, S Schulz
Proceedings of the 18th ACM Conference on Recommender Systems, 2024
12024
e-fold cross-validation: A computing and energy-efficient alternative to k-fold cross-validation with adaptive folds
J Beel, L Wegmeth, T Vente
OSF, 2024
12024
Improving Recommender Systems Through the Automation of Design Decisions
L Wegmeth
Proceedings of the 17th ACM Conference on Recommender Systems, 1332-1338, 2023
12023
Greedy Ensemble Selection for Top-N Recommendations
T Vente, Z Mehta, L Wegmeth, J Beel
RobustRecSys: Design, Evaluation and Deployment of Robust Recommender Systems, 2024
2024
Removing Bad Influence: Identifying and Pruning Detrimental Users in Collaborative Filtering Recommender Systems
P Meister, L Wegmeth, T Vente, J Beel
RobustRecSys: Design, Evaluation and Deployment of Robust Recommender Systems, 2024
2024
Recommender Systems Algorithm Selection for Ranking Prediction on Implicit Feedback Datasets
L Wegmeth, T Vente, J Beel
Proceedings of the 18th ACM Conference on Recommender Systems, 2024
2024
Revealing the Hidden Impact of Top-N Metrics on Optimization in Recommender Systems
L Wegmeth, T Vente, L Purucker
European Conference on Information Retrieval, 140-156, 2024
2024
The Challenges of Algorithm Selection and Hyperparameter Optimization for Recommender Systems
L Wegmeth, T Vente, J Beel
COSEAL Workshop 2023 http://dx.doi.org/10.13140/RG.2.2.24089.19049, 2023
2023
Cooperative Meta-Learning Service for Recommender Systems
L Wegmeth, J Beel
COSEAL Workshop 2022 http://dx.doi.org/10.13140/RG.2.2.10667.41768, 2022
2022
Checky, the Paper-Submission Checklist Generator for Authors, Reviewers and LLMs
J Beel, B Gipp, D Jannach, A Said, L Wegmeth, T Vente
47th European Conference on Information Retrieval (ECIR), 0
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