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Maystre, Lucas
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1

Accelerating Creator Audience Building through Centralized ..:

, In: Proceedings of the 17th ACM Conference on Recommender Systems,
Baran, Buket ; Junior, Guilherme Dinis ; Danylenko, Antonina... - p. 70-73 , 2023
Link: https://dl.acm.org/doi/1..
 
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2

Impatient Bandits: Optimizing Recommendations for the Long-..:

, In: Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining,
McDonald, Thomas M. ; Maystre, Lucas ; Lalmas, Mounia.. - p. 1687-1697 , 2023
Link: https://dl.acm.org/doi/1..
 
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3

Using Survival Models to Estimate User Engagement in Online..:

, In: Proceedings of the ACM Web Conference 2022,
Chandar, Praveen ; St. Thomas, Brian ; Maystre, Lucas... - p. 3186-3195 , 2022
Link: https://dl.acm.org/doi/1..
 
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4

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

, In: Machine Learning and Knowledge Discovery in Databases. Research Track; Lecture Notes in Computer Science,
Bütepage, Judith ; Maystre, Lucas ; Lalmas, Mounia - p. 84-99 , 2021
Link: https://doi.org/10.1007/..
 
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5

Shifting Consumption towards Diverse Content on Music Strea..:

, In: Proceedings of the 14th ACM International Conference on Web Search and Data Mining,
Hansen, Christian ; Mehrotra, Rishabh ; Hansen, Casper... - p. 238-246 , 2021
Link: https://dl.acm.org/doi/1..
 
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6

Where To Next? A Dynamic Model of User Preferences:

, In: Proceedings of the Web Conference 2021,
Sanna Passino, Francesco ; Maystre, Lucas ; Moor, Dmitrii.. - p. 3210-3220 , 2021
Link: https://dl.acm.org/doi/1..
 
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7

Contextual and Sequential User Embeddings for Large-Scale M..:

, In: Fourteenth ACM Conference on Recommender Systems,
Hansen, Casper ; Hansen, Christian ; Maystre, Lucas... - p. 53-62 , 2020
Link: https://dl.acm.org/doi/1..
 
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8

Algorithmic Effects on the Diversity of Consumption on Spot..:

, In: Proceedings of The Web Conference 2020,
Anderson, Ashton ; Maystre, Lucas ; Anderson, Ian.. - p. 2155-2165 , 2020
Link: https://dl.acm.org/doi/1..
 
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9

Pairwise Comparisons with Flexible Time-Dynamics:

, In: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining,
Maystre, Lucas ; Kristof, Victor ; Grossglauser, Matthias - p. 1236-1246 , 2019
Link: https://dl.acm.org/doi/1..
 
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10

Can Who-Edits-What Predict Edit Survival?:

, In: Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining,
Yardim, Ali Batuhan ; Kristof, Victor ; Maystre, Lucas. - p. 2604-2613 , 2018
Link: https://dl.acm.org/doi/1..
 
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11

Impatient Bandits: Optimizing Recommendations for the Long-..:

McDonald, Thomas M ; Maystre, Lucas ; Lalmas, Mounia..
http://arxiv.org/abs/2307.09943.  , 2023
Link: http://arxiv.org/abs/230..
 
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12

Fast Interactive Search with a Scale-Free Comparison Oracle:

Chumbalov, Daniyar ; Klein, Lars ; Maystre, Lucas.
http://arxiv.org/abs/2306.01814.  , 2023
Link: http://arxiv.org/abs/230..
 
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13

A Strong Baseline for Batch Imitation Learning:

Smith, Matthew ; Maystre, Lucas ; Dai, Zhenwen.
http://arxiv.org/abs/2302.02788.  , 2023
Link: http://arxiv.org/abs/230..
 
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14

Estimating long-term causal effects from short-term experim..:

Van Goffrier, Graham ; Maystre, Lucas ; Gilligan-Lee, Ciarán
http://arxiv.org/abs/2302.10625.  , 2023
Link: http://arxiv.org/abs/230..
 
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15

Optimizing Audio Recommendations for the Long-Term: A Reinf..:

Maystre, Lucas ; Russo, Daniel ; Zhao, Yu
http://arxiv.org/abs/2302.03561.  , 2023
Link: http://arxiv.org/abs/230..
 
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