Publications

Oct 23, 2023|CIKM
Exploiting Sequential Music Preferences via Optimisation-Based Sequencing
Dmitrii Moor, Yi Yuan, Rishabh Mehrotra, Zhenwen Dai, Mounia Lalmas
Jul 23, 2023|KDD
Impatient Bandits: Optimizing for the Long-Term Without Delay
Thomas McDonald, Lucas Maystre, Mounia Lalmas, Daniel Russo, Kamil Ciosek
Jul 19, 2023|KDD
Automatic Music Playlist Generation via Simulation-based Reinforcement Learning
Federico Tomasi, Joseph Cauteruccio, Surya Kanoria, Kamil Ciosek, Matteo Rinaldi, Zhenwen Dai
Mar 23, 2023|Frontier on Big Data: Recommender Systems
A Survey on Multi-objective Recommender Systems
Dietmar Jannach and Himan Abdollahpouri
Mar 21, 2023|Intelligent User Interfaces (IUI)
Enabling Goal-Focused Exploration of Podcasts in Interactive Recommender Systems
Yu Liang, Aditya Ponnada, Paul Lamere, Nediyana Daskalova
Feb 21, 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
Nov 18, 2022|NeurIPS
Temporally-Consistent Survival Analysis
Lucas Maystre, Daniel Russo
Aug 2, 2022|UAI
Multistate analysis with infinite mixtures of Markov chains
Lucas Maystre, Tiffany Wu, Roberto Sanchis-Ojeda, Tony Jebara
Jun 7, 2022|ICWSM
Time after Time: Longitudinal Trends in Nostalgic Listening
Clara Hanson, Jesse Anderton, Samuel F. Way, Ian Anderson, Scott Wolf, Alice Wang
Jun 7, 2022|ICWSM
The Dynamics of Exploration on Spotify
Lillio Mok, Samuel F. Way, Lucas Maystre, Ashton Anderson
Apr 26, 2022|The Web Conference (WWW)
Mostra: A Flexible Balancing Framework to Trade-off User, Artist and Platform Objectives for Music Sequencing
Emanuele Bugliarello, Rishabh Mehrotra, James Kirk, Mounia Lalmas
Mar 18, 2022|Intelligent User Interfaces (IUI)
TastePaths: Enabling deeper exploration and understanding of personal preferences in recommender systems
Savvas Petridis, Nediyana Daskalova, Sarah Mennicken, Samuel F. Way, Paul Lamere, Jennifer Thom
Jul 26, 2021|ACL
Modeling Language Usage and Listener Engagement in Podcasts
Sravana Reddy, Mariya Lazarova, Yongze Yu, Rosie Jones
Apr 19, 2021|The Web Conference
Where To Next? A Dynamic Model of User Preferences
Francesco Sanna Passino, Lucas Maystre, Dmitrii Moor, Ashton Anderson, Mounia Lalmas
Apr 12, 2021|AISTATS
Collaborative Classification from Noisy Labels
Lucas Maystre, Nagarjuna Kumarappan, Judith Bütepage, Mounia Lalmas
Sep 22, 2020|RecSys
Contextual and Sequential User Embeddings for Large-Scale Music Recommendation
Casper Hansen, Christian Hansen, Lucas Maystre, Rishabh Mehrotra, Brian Brost, Federico Tomasi, Mounia Lalmas
Sep 22, 2020|RecSys
Inferring the Causal Impact of New Track Releases on Music Recommendation Platforms through Counterfactual Predictions
Rishabh Mehrotra, Prasanta Bhattacharya, Mounia Lalmas
Sep 22, 2020|RecSys
Investigating Listeners’ Responses to Divergent Recommendations
Rishabh Mehrotra, Chirag Shah, Benjamin Carterette
Jul 25, 2020|SIGIR
Recommending Podcasts for Cold-Start Users Based on Music Listening and Taste
Zahra Nazari, Christophe Charbuillet, Johan Pages, Martin Laurent, Denis Charrier, Briana Vecchione, Ben Carterette
Jul 13, 2020|EC
The Engagement-Diversity Connection: Evidence from a Field Experiment on Spotify
David Holtz, Benjamin Carterette, Praveen Chandar, Zahra Nazari, Henriette Cramer, Sinan Aral

Explore our publications and scientific contributions

Exploiting Sequential Music Preferences via Optimisation-Based Sequencing

Impatient Bandits: Optimizing for the Long-Term Without Delay

Automatic Music Playlist Generation via Simulation-based Reinforcement Learning

A Survey on Multi-objective Recommender Systems

Enabling Goal-Focused Exploration of Podcasts in Interactive Recommender Systems

Calibrated Recommendations as a Minimum-Cost Flow Problem

Temporally-Consistent Survival Analysis

Multistate analysis with infinite mixtures of Markov chains

Time after Time: Longitudinal Trends in Nostalgic Listening

The Dynamics of Exploration on Spotify

Mostra: A Flexible Balancing Framework to Trade-off User, Artist and Platform Objectives for Music Sequencing

TastePaths: Enabling deeper exploration and understanding of personal preferences in recommender systems

Modeling Language Usage and Listener Engagement in Podcasts

Where To Next? A Dynamic Model of User Preferences

Collaborative Classification from Noisy Labels

Contextual and Sequential User Embeddings for Large-Scale Music Recommendation

Inferring the Causal Impact of New Track Releases on Music Recommendation Platforms through Counterfactual Predictions

Investigating Listeners’ Responses to Divergent Recommendations

Recommending Podcasts for Cold-Start Users Based on Music Listening and Taste

The Engagement-Diversity Connection: Evidence from a Field Experiment on Spotify