35 citations · 36 across the 5 of their papers we have counts for
5 papers
Exploring Large Action Sets with Hyperspherical Embeddings using von Mises-Fisher Sampling
Walid Bendada, Guillaume Salha-Galvan, Romain Hennequin +3
This paper introduces von Mises-Fisher exploration (vMF-exp), a scalable method for exploring large action sets in reinforcement learning problems where hyperspherical embedding ve…
Let's Get It Started: Fostering the Discoverability of New Releases on Deezer
Léa Briand, Théo Bontempelli, Walid Bendada +5
This paper presents our recent initiatives to foster the discoverability of new releases on the music streaming service Deezer. After introducing our search and recommendation feat…
Track Mix Generation on Music Streaming Services using Transformers
Walid Bendada, Théo Bontempelli, Mathieu Morlon +4
This paper introduces Track Mix, a personalized playlist generation system released in 2022 on the music streaming service Deezer. Track Mix automatically generates "mix" playlists…
Flow Moods: Recommending Music by Moods on Deezer
Théo Bontempelli, Benjamin Chapus, François Rigaud +3
The music streaming service Deezer extensively relies on its Flow algorithm, which generates personalized radio-style playlists of songs, to help users discover musical content. No…
Carousel Personalization in Music Streaming Apps with Contextual Bandits
Walid Bendada, Guillaume Salha, Théo Bontempelli
Media services providers, such as music streaming platforms, frequently leverage swipeable carousels to recommend personalized content to their users. However, selecting the most r…