Lucas Maystre

46 papers A* 10A 7C 1Journal 21Unranked 5
YearRankTypeTitle / Venue / Authors
2025 — conf
From Characters to Tokens: Dynamic Grouping with Hierarchical BPE.
EMNLP (Findings)
Rares Dolga, Lucas Maystre, Tudor Berariu, David Barber
2025 J jnl
From Characters to Tokens: Dynamic Grouping with Hierarchical BPE.
CoRR
Rares Dolga, Lucas Maystre, Tudor Berariu, David Barber
2025 J jnl
Impatient Bandits: Optimizing for the Long-Term Without Delay.
CoRR
Kelly W. Zhang, Thomas Baldwin-McDonald, Kamil Ciosek, Lucas Maystre, Daniel Russo
2025 J jnl
Incremental Sequence Classification with Temporal Consistency.
CoRR
Lucas Maystre, Gabriel Barello, Tudor Berariu, Aleix Cambray, Rares Dolga, Alvaro Ortega Gonzalez, Andrei Cristian Nica, David Barber
2025 J jnl
Toward Autonomous UI Exploration: The UIExplorer Benchmark.
CoRR
Andrei Cristian Nica, Akshaya Vishnu Kudlu Shanbhogue, Harshil Shah, Aleix Cambray, Tudor Berariu, Lucas Maystre, David Barber
2025 J jnl
Unifying Linear-Time Attention via Latent Probabilistic Modelling.
Trans. Mach. Learn. Res.
Rares Dolga, Lucas Maystre, Marius Cobzarenco, David Barber
2025 J jnl
When Embedding Models Meet: Procrustes Bounds and Applications.
CoRR
Lucas Maystre, Alvaro Ortega Gonzalez, Charles Park, Rares Dolga, Tudor Berariu, Yu Zhao, Kamil Ciosek
2024 A conf
Fast Interactive Search under a Scale-Free Comparison Oracle.
UAI
Daniyar Chumbalov, Lars Klein, Lucas Maystre, Matthias Grossglauser
2024 J jnl
On the Importance of Uncertainty in Decision-Making with Large Language Models.
CoRR
Nicolò Felicioni, Lucas Maystre, Sina Ghiassian, Kamil Ciosek
2024 J jnl
On the Importance of Uncertainty in Decision-Making with Large Language Models.
Trans. Mach. Learn. Res.
Nicolò Felicioni, Lucas Maystre, Sina Ghiassian, Kamil Ciosek
2023 J jnl
A Strong Baseline for Batch Imitation Learning.
CoRR
Matthew Smith, Lucas Maystre, Zhenwen Dai, Kamil Ciosek
2023 A conf
Accelerating Creator Audience Building through Centralized Exploration.
RecSys
Buket Baran, Guilherme Dinis Junior, Antonina Danylenko, Olayinka S. Folorunso, Gösta Forsum, Maksym Lefarov, Lucas Maystre, Yu Zhao
2023 — conf
Estimating long-term causal effects from short-term experiments and long-term observational data with unobserved confounding.
CLeaR
Graham W. Van Goffrier, Lucas Maystre, Ciarán Mark Gilligan-Lee
2023 J jnl
Estimating long-term causal effects from short-term experiments and long-term observational data with unobserved confounding.
CoRR
Graham W. Van Goffrier, Lucas Maystre, Ciarán M. Gilligan-Lee
2023 J jnl
Fast Interactive Search with a Scale-Free Comparison Oracle.
CoRR
Daniyar Chumbalov, Lars Klein, Lucas Maystre, Matthias Grossglauser
2023 A* conf
Impatient Bandits: Optimizing Recommendations for the Long-Term Without Delay.
KDD
Thomas M. McDonald, Lucas Maystre, Mounia Lalmas, Daniel Russo, Kamil Ciosek
2023 J jnl
Impatient Bandits: Optimizing Recommendations for the Long-Term Without Delay.
CoRR
Thomas M. McDonald, Lucas Maystre, Mounia Lalmas, Daniel Russo, Kamil Ciosek
2023 J jnl
Optimizing Audio Recommendations for the Long-Term: A Reinforcement Learning Perspective.
CoRR
Lucas Maystre, Daniel Russo, Yu Zhao
2022 A conf
Multistate analysis with infinite mixtures of Markov chains.
UAI
Lucas Maystre, Tiffany Wu, Roberto Sanchis-Ojeda, Tony Jebara
2022 A* conf
Temporally-Consistent Survival Analysis.
NeurIPS
Lucas Maystre, Daniel Russo
2022 A conf
The Dynamics of Exploration on Spotify.
ICWSM
Lillio Mok, Samuel F. Way, Lucas Maystre, Ashton Anderson
2022 A* conf
Using Survival Models to Estimate User Engagement in Online Experiments.
WWW
Praveen Chandar, Brian St. Thomas, Lucas Maystre, Vijay Pappu, Roberto Sanchis-Ojeda, Tiffany Wu, Ben Carterette, Mounia Lalmas, Tony Jebara
2021 A conf
Collaborative Classification from Noisy Labels.
AISTATS
Lucas Maystre, Nagarjuna Kumarappan, Judith Bütepage, Mounia Lalmas
2021 — conf
Gaussian Process Encoders: VAEs with Reliable Latent-Space Uncertainty.
ECML/PKDD (2)
Judith Bütepage, Lucas Maystre, Mounia Lalmas
2021 A conf
Shifting Consumption towards Diverse Content on Music Streaming Platforms.
WSDM
Christian Hansen, Rishabh Mehrotra, Casper Hansen, Brian Brost, Lucas Maystre, Mounia Lalmas
2021 A* conf
Where To Next? A Dynamic Model of User Preferences.
WWW
Francesco Sanna Passino, Lucas Maystre, Dmitrii Moor, Ashton Anderson, Mounia Lalmas
2020 A* conf
Algorithmic Effects on the Diversity of Consumption on Spotify.
WWW
Ashton Anderson, Lucas Maystre, Ian Anderson, Rishabh Mehrotra, Mounia Lalmas
2020 A conf
Contextual and Sequential User Embeddings for Large-Scale Music Recommendation.
RecSys
Casper Hansen, Christian Hansen, Lucas Maystre, Rishabh Mehrotra, Brian Brost, Federico Tomasi, Mounia Lalmas
2020 A* conf
Scalable and Efficient Comparison-based Search without Features.
ICML
Daniyar Chumbalov, Lucas Maystre, Matthias Grossglauser
2019 J jnl
A User Study of Perceived Carbon Footprint.
CoRR
Victor Kristof, Valentin Quelquejay-Leclère, Robin Zbinden, Lucas Maystre, Matthias Grossglauser, Patrick Thiran
2019 J jnl
Learning to Search Efficiently Using Comparisons.
CoRR
Daniyar Chumbalov, Lucas Maystre, Matthias Grossglauser
2019 J jnl
Linear-Time Inference for Pairwise Comparisons with Gaussian-Process Dynamics.
CoRR
Lucas Maystre, Victor Kristof, Matthias Grossglauser
2019 A* conf
Pairwise Comparisons with Flexible Time-Dynamics.
KDD
Lucas Maystre, Victor Kristof, Matthias Grossglauser
2018 A* conf
Can Who-Edits-What Predict Edit Survival?
KDD
Ali Batuhan Yardim, Victor Kristof, Lucas Maystre, Matthias Grossglauser
2018 J jnl
Can Who-Edits-What Predict Edit Survival?
CoRR
Ali Batuhan Yardim, Victor Kristof, Lucas Maystre, Matthias Grossglauser
2018 — —
Efficient Learning from Comparisons.
Lucas Maystre
2018 — ch.
Efficient Learning from Comparisons.
Ausgezeichnete Informatikdissertationen
Lucas Maystre
2017 A* conf
ChoiceRank: Identifying Preferences from Node Traffic in Networks.
ICML
Lucas Maystre, Matthias Grossglauser
2017 A* conf
Just Sort It! A Simple and Effective Approach to Active Preference Learning.
ICML
Lucas Maystre, Matthias Grossglauser
2016 J jnl
ChoiceRank: Identifying Preferences from Node Traffic in Networks.
CoRR
Lucas Maystre, Matthias Grossglauser
2016 C conf
Collaborative Recurrent Neural Networks for Dynamic Recommender Systems.
ACML
Young-Jun Ko, Lucas Maystre, Matthias Grossglauser
2016 — conf
The Player Kernel: Learning Team Strengths Based on Implicit Player Contributions.
MLSA@PKDD/ECML
Lucas Maystre, Victor Kristof, Antonio J. González Ferrer, Matthias Grossglauser
2016 J jnl
The Player Kernel: Learning Team Strengths Based on Implicit Player Contributions.
CoRR
Lucas Maystre, Victor Kristof, Antonio J. González Ferrer, Matthias Grossglauser
2015 — conf
Fast and Accurate Inference of Plackett-Luce Models.
NIPS
Lucas Maystre, Matthias Grossglauser
2015 J jnl
Robust Active Ranking from Sparse Noisy Comparisons.
CoRR
Lucas Maystre, Matthias Grossglauser
2013 J jnl
Mitigating Epidemics through Mobile Micro-measures.
CoRR
Mohamed Kafsi, Ehsan Kazemi, Lucas Maystre, Lyudmila Yartseva, Matthias Grossglauser, Patrick Thiran