57 citations · 61 across the 4 of their papers we have counts for
4 papers
Adopting State-of-the-Art Pretrained Audio Representations for Music Recommender Systems
Yan-Martin Tamm, Anna Aljanaki
Over the years, Music Information Retrieval (MIR) research community has released various models pretrained on large amounts of music data. Transfer learning showcases the proven e…
Leveraging Artist Catalogs for Cold-Start Music Recommendation
Yan-Martin Tamm, Gregor Meehan, Vojtěch Nekl +4
The item cold-start problem poses a fundamental challenge for music recommendation: newly added tracks lack the interaction history that collaborative filtering (CF) requires. Exis…
Comparative Analysis of Pretrained Audio Representations in Music Recommender Systems
Yan-Martin Tamm, Anna Aljanaki
Over the years, Music Information Retrieval (MIR) has proposed various models pretrained on large amounts of music data. Transfer learning showcases the proven effectiveness of pre…
Quality Metrics in Recommender Systems: Do We Calculate Metrics Consistently?
Yan-Martin Tamm, Rinchin Damdinov, Alexey Vasilev
Offline evaluation is a popular approach to determine the best algorithm in terms of the chosen quality metric. However, if the chosen metric calculates something unexpected, this…