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

March 2023 | Nature Machine Intelligence

Estimating categorical counterfactuals via deep twin networks

Athanasios Vlontzos, Bernhard Kainz, Ciarán M. Gilligan-Lee

February 2023 | WSDM

Calibrated Recommendations as a Minimum-Cost Flow Problem

Himan Abdollahpouri, Zahra Nazari, Alex Gain,Clay Giibson, Maria Dimakopoulou, Jesse Anderton, Benjamin Carterette, Mounia Lalmas, Tony Jebara

November 2022 | NeurIPS

Society of Agents: Regrets Bounds of Concurrent Thompson Sampling

Yan Chen, Perry Dong, Qinxun Bai, Maria Dimakopoulou, Wei Xu, Zhengyuan Zhou

Other Research Areas