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Dominik Kowald

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The Impact of Differential Privacy on Recommendation Accuracy and Popularity Bias

Jan 15, 2024
Peter Müllner, Elisabeth Lex, Markus Schedl, Dominik Kowald

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Take the aTrain. Introducing an Interface for the Accessible Transcription of Interviews

Oct 18, 2023
Armin Haberl, Jürgen Fleiß, Dominik Kowald, Stefan Thalmann

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Beyond-Accuracy: A Review on Diversity, Serendipity and Fairness in Recommender Systems Based on Graph Neural Networks

Oct 03, 2023
Tomislav Duricic, Dominik Kowald, Emanuel Lacic, Elisabeth Lex

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Reproducibility in Machine Learning-Driven Research

Jul 19, 2023
Harald Semmelrock, Simone Kopeinik, Dieter Theiler, Tony Ross-Hellauer, Dominik Kowald

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A Study on Accuracy, Miscalibration, and Popularity Bias in Recommendations

Mar 01, 2023
Dominik Kowald, Gregor Mayr, Markus Schedl, Elisabeth Lex

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A conceptual model for leaving the data-centric approach in machine learning

Feb 07, 2023
Sebastian Scher, Bernhard Geiger, Simone Kopeinik, Andreas Trügler, Dominik Kowald

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Uptrendz: API-Centric Real-time Recommendations in Multi-Domain Settings

Jan 03, 2023
Emanuel Lacic, Tomislav Duricic, Leon Fadljevic, Dieter Theiler, Dominik Kowald

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Long-term dynamics of fairness: understanding the impact of data-driven targeted help on job seekers

Aug 17, 2022
Sebastian Scher, Simone Kopeinik, Andreas Trügler, Dominik Kowald

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ReuseKNN: Neighborhood Reuse for Privacy-Aware Recommendations

Jun 23, 2022
Peter Müllner, Markus Schedl, Elisabeth Lex, Dominik Kowald

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Recommendations in a Multi-Domain Setting: Adapting for Customization, Scalability and Real-Time Performance

Mar 02, 2022
Emanuel Lacic, Dominik Kowald

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