The latest papers from CAIL folks and their co-authors. You’ll see a massive presence at NeurIPS’24: congrats!!!
Neurips – Vancouver, Canada
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Otmane Sakhi (Criteo AI Lab), Imad Aouali (Criteo AI Lab, CREST-ENSAE), Pierre Alquier (ESSEC Business School), and Nicolas Chopin (CREST-ENSAE). Logarithmic Smoothing for Pessimistic Off-Policy Evaluation, Selection and Learning. In Neurips 2024 (Spotlight).
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Felipe Garrido* (FAIRPLAY, CREST-ENSAE), Benjamin Heymann* (Criteo AI Lab), Maxime Vono* (Criteo AI Lab), Vianney Perchet (Criteo AI Lab / ENSAE), Patrick Loiseau (FAIRPLAY Inria). DU-Shapley: A Shapley Value Proxy for Efficient Dataset Valuation. In NeurIPS 2024.
- Dorian Baudry* (ENSAE), Hugo Richard* (Criteo), Maria Cherifa* (Criteo), Vianney Perchet (Criteo / ENSAE), Clement Calauzènes (Criteo). Optimizing the coalition gain in Online Auctions with Greedy Structured Bandits in NeurIPS 2024.
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Marius Potfer* (ENSAE), Dorian Baudry (ENSAE), Hugo Richard (Criteo), Vianney Perchet (Criteo / ENSAE), Cheng Wang (EDF). Improved learning rates in multi-unit uniform price auctions in NeurIPS 2024.
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Mariia Vladimirova (Criteo), Federico Pavone (Paris-Dauphine), Eustache Diement (Criteo). FairJob: A Real-World Dataset for Fairness in Online Systems in NeurIPS 2024.
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Julien Zhou (Criteo), Pierre Gaillard (Inria), Thibaud Rahier (Criteo), Houssam Zenati (Former Criteo, current Inria), Julyan Arbel (Inria). Towards Efficient and Optimal Covariance-Adaptive Algorithms for Combinatorial Semi-Bandits in NeurIPS 2024.
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Ahmed Ben Yahmed (Criteo), Clément Calauzènes (Criteo), Vianney Perchet (Criteo / ENSAE). Strategic Multi-Armed Bandit Problems Under Debt-Free Reporting in NeurIPS 2024.
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Louis Serrano, Thomas X Wang, Etienne Le Naour, Jean-Noël Vittaut, Patrick Gallinari, AROMA: Preserving Spatial Structure for Latent PDE Modeling with Local Neural Fields, NeurIPS 2024.
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Armand Kassaï Koupaï, Jorge Mifsut Benet, Yuan Yin, Jean-Noël Vittaut, Patrick Gallinari, Boosting Generalization in Parametric PDE Neural Solvers through Adaptive Conditioning, NeurIPS 2024.
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Mouadh Yagoubi, David Danan, Milad Leyli-abadi, Jean-Patrick Brunet, Jocelyn Ahmed Mazari, Florent Bonnet, maroua gmati, Asma Farjallah, Paola Cinnella, Patrick Gallinari, Marc Schoenauer, NeurIPS 2024 ML4CFD Competition: Harnessing Machine Learning for Computational Fluid Dynamics in Airfoil Design, NeurIPS 2024.
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Côme Fiegel, Pierre Ménard, Tadashi Kozuno, Remi Munos, Vianney Perchet, Michal Valko. Local and Adaptive Mirror Descents in Extensive-Form Games NeurIPS 2024.
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Ziyad Benomar, Dorian Baudry, Vianney Perchet. Lookback Prophet Inequalitites NeurIPS 2024.
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Nadav Merlis, Dorian Baudry, Vianney Perchet. The Value of Reward Lookahead in Reinforcement Learning NeurIPS 2024.
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Matilde Tullii, Solenne Gaucher, Nadav Merlis, Vianney Perchet. Improved Algorithms for Contextual Dynamic Pricing NeurIPS 2024.
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Ziyad Benomar, Evgenii Chzhen, Nicolas Schreuder, Vianney Perchet. Addressing bias in online selection with limited budget of comparisons NeurIPS 2024.
ECML – Vilnius, Lithuania
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David Rohde (industry track) Why the Shooting in the Dark Method Dominates Recommender Systems Practice
RecSys – Bari, Italy
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David Rohde (industry track) Why the Shooting in the Dark Method Dominates Recommender Systems Practice
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Flavian Vasile (workshop organizer) CONSEQUENCES
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RecSys/CONSEQUENCES (workshop paper)
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Otmane Sakhi, Imad Aouali, Pierre Alquier and Nicolas Chopin. Logarithmic Smoothing for Pessimistic Off-Policy Evaluation, Selection and Learning
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RecSys SURE (workshop paper)
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Benjamin Heymann, Flavian Vasile and David Rohde. Welfare-Optimized Recommender Systems
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WISE – Doha, Qatar
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Matilde Tullii* (FAIRPLAY Inria), Solenne Gaucher* (FAIRPLAY Inria), Hugo Richard* (Criteo AI Lab), Eustache Diemert (Criteo AI Lab), Vianney Perchet (Criteo AI Lab, FAIRPLAY Inria), Alain Rakotomamonjy (Criteo AI Lab), Clément Calauzènes (Criteo AI Lab), and Maxime Vono (Criteo AI Lab). Open Research Challenges for Private Advertising Systems under Local Differential Privacy in WISE 2024.
WINE – Edinburgh, UK
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Benjamin Heymann, Alexandre Gilotte, Rémi Chan-Renous Repeated Bidding with Dynamic Value
SODA – New Orleans, US
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Mathieu Molina, Patrick Loiseau, Vianney Perchet. Prophet Inequalities: Competing with the Top $\ell$ Items is Easy.