Lucas Maystre

According to our database, Lucas Maystre authored at least 32 papers between 2013 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

On the Importance of Uncertainty in Decision-Making with Large Language Models.

Nicolò Felicioni, Lucas Maystre, Sina Ghiassian, Kamil Ciosek

Trans. Mach. Learn. Res., 2024

2023

Fast Interactive Search with a Scale-Free Comparison Oracle.

Daniyar Chumbalov, Lars Klein, Lucas Maystre, Matthias Grossglauser

CoRR, 2023

Optimizing Audio Recommendations for the Long-Term: A Reinforcement Learning Perspective.

Lucas Maystre, Daniel Russo, Yu Zhao

CoRR, 2023

A Strong Baseline for Batch Imitation Learning.

Matthew Smith, Lucas Maystre, Zhenwen Dai, Kamil Ciosek

CoRR, 2023

Accelerating Creator Audience Building through Centralized Exploration.

Buket Baran, Guilherme Dinis Junior, Antonina Danylenko, Olayinka S. Folorunso, Gösta Forsum, Maksym Lefarov, Lucas Maystre, Yu Zhao

Proceedings of the 17th ACM Conference on Recommender Systems, 2023

Impatient Bandits: Optimizing Recommendations for the Long-Term Without Delay.

Thomas M. McDonald, Lucas Maystre, Mounia Lalmas, Daniel Russo, Kamil Ciosek

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Estimating long-term causal effects from short-term experiments and long-term observational data with unobserved confounding.

Graham W. Van Goffrier, Lucas Maystre, Ciarán Mark Gilligan-Lee

Proceedings of the Conference on Causal Learning and Reasoning, 2023

2022

Using Survival Models to Estimate User Engagement in Online Experiments.

Praveen Chandar, Brian St. Thomas, Lucas Maystre, Vijay Pappu, Roberto Sanchis-Ojeda, Tiffany Wu, Ben Carterette, Mounia Lalmas, Tony Jebara

Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

Multistate analysis with infinite mixtures of Markov chains.

Lucas Maystre, Tiffany Wu, Roberto Sanchis-Ojeda, Tony Jebara

Proceedings of the Uncertainty in Artificial Intelligence, 2022

Temporally-Consistent Survival Analysis.

Lucas Maystre, Daniel Russo

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

The Dynamics of Exploration on Spotify.

Lillio Mok, Samuel F. Way, Lucas Maystre, Ashton Anderson

Proceedings of the Sixteenth International AAAI Conference on Web and Social Media, 2022

2021

Where To Next? A Dynamic Model of User Preferences.

Francesco Sanna Passino, Lucas Maystre, Dmitrii Moor, Ashton Anderson, Mounia Lalmas

Proceedings of the WWW '21: The Web Conference 2021, 2021

Shifting Consumption towards Diverse Content on Music Streaming Platforms.

Christian Hansen, Rishabh Mehrotra, Casper Hansen, Brian Brost, Lucas Maystre, Mounia Lalmas

Proceedings of the WSDM '21, 2021

Gaussian Process Encoders: VAEs with Reliable Latent-Space Uncertainty.

Judith Bütepage, Lucas Maystre, Mounia Lalmas

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

Collaborative Classification from Noisy Labels.

Lucas Maystre, Nagarjuna Kumarappan, Judith Bütepage, Mounia Lalmas

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Algorithmic Effects on the Diversity of Consumption on Spotify.

Ashton Anderson, Lucas Maystre, Ian Anderson, Rishabh Mehrotra, Mounia Lalmas

Proceedings of the WWW '20: The Web Conference 2020, Taipei, Taiwan, April 20-24, 2020, 2020

Contextual and Sequential User Embeddings for Large-Scale Music Recommendation.

Casper Hansen, Christian Hansen, Lucas Maystre, Rishabh Mehrotra, Brian Brost, Federico Tomasi, Mounia Lalmas

Proceedings of the RecSys 2020: Fourteenth ACM Conference on Recommender Systems, 2020

Scalable and Efficient Comparison-based Search without Features.

Daniyar Chumbalov, Lucas Maystre, Matthias Grossglauser

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

A User Study of Perceived Carbon Footprint.

Victor Kristof, Valentin Quelquejay-Leclère, Robin Zbinden, Lucas Maystre, Matthias Grossglauser, Patrick Thiran

CoRR, 2019

Learning to Search Efficiently Using Comparisons.

Daniyar Chumbalov, Lucas Maystre, Matthias Grossglauser

CoRR, 2019

Linear-Time Inference for Pairwise Comparisons with Gaussian-Process Dynamics.

Lucas Maystre, Victor Kristof, Matthias Grossglauser

CoRR, 2019

Pairwise Comparisons with Flexible Time-Dynamics.

Lucas Maystre, Victor Kristof, Matthias Grossglauser

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

2018

Efficient Learning from Comparisons.

Lucas Maystre

Proceedings of the Ausgezeichnete Informatikdissertationen 2018., 2018

Efficient Learning from Comparisons.

Lucas Maystre

PhD thesis, 2018

Can Who-Edits-What Predict Edit Survival?

Ali Batuhan Yardim, Victor Kristof, Lucas Maystre, Matthias Grossglauser

Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

2017

ChoiceRank: Identifying Preferences from Node Traffic in Networks.

Lucas Maystre, Matthias Grossglauser

Proceedings of the 34th International Conference on Machine Learning, 2017

Just Sort It! A Simple and Effective Approach to Active Preference Learning.

Lucas Maystre, Matthias Grossglauser

Proceedings of the 34th International Conference on Machine Learning, 2017

2016

The Player Kernel: Learning Team Strengths Based on Implicit Player Contributions.

Lucas Maystre, Victor Kristof, Antonio J. González Ferrer, Matthias Grossglauser

Proceedings of the Workshop on Machine Learning and Data Mining for Sports Analytics 2016 co-located with the 2016 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2016

Collaborative Recurrent Neural Networks for Dynamic Recommender Systems.

Young-Jun Ko, Lucas Maystre, Matthias Grossglauser

Proceedings of The 8th Asian Conference on Machine Learning, 2016

2015

Robust Active Ranking from Sparse Noisy Comparisons.

Lucas Maystre, Matthias Grossglauser

CoRR, 2015

Fast and Accurate Inference of Plackett-Luce Models.

Lucas Maystre, Matthias Grossglauser

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2013

Mitigating Epidemics through Mobile Micro-measures.

Mohamed Kafsi, Ehsan Kazemi, Lucas Maystre, Lyudmila Yartseva, Matthias Grossglauser, Patrick Thiran

CoRR, 2013