Machine Learning

Machine learning touches every aspect of Spotify’s business. It is used to help listeners discover content via recommendations and search, generate playlists, extract audio content-rich signals for cataloging and other content-based applications, understanding voice commands, serve ads, develop business metrics and optimization algorithms, create music with AI-assisted tools, and more. Central to these endeavors is a commitment to cultivate expertise in the latest approaches as we advance the state of the art in machine learning methodology and applications. Of particular interest are approaches in reinforcement learning, approximate inference, graphical models, causal inference, deep learning, time series modeling, and meta-model learning.

Latest Machine Learning Publications

November 2023 | ACM TORS

Unbiased Identification of Broadly Appealing Content Using a Pure Exploration Infinitely-Armed Bandit Strategy

Maryam Aziz, Jesse Anderton, Kevin Jamieson, Alice Wang, Hugues Bouchard, Javed Aslam

October 2023 | CIKM

Graph Learning for Exploratory Query Suggestions in an Instant Search System

Enrico Palumbo, Andreas Damianou, Alice Wang, Alva Liu, Ghazal Fazelnia, Francesco Fabbri, Rui Ferreira, Fabrizio Silvestri, Hugues Bouchard, Claudia Hauff, Mounia Lalmas, Ben Carterette, Praveen Chandar, David Nyhan

September 2023 | CLEF

Cem Mil Podcasts: A Spoken Portuguese Document Corpus For Multi-modal, Multi-lingual and Multi-Dialect Information Access Research

Ekaterina Garmash, Edgar Tanaka, Ann Clifton, Joana Correia, Sharmistha Jat, Winstead Zhu, Rosie Jones, Jussi Karlgren

Other Research Areas