Ensemble Feature Ranking. - Kees Jong; Jérémie Mary; Antoine Cornuéjols; Elena Marchiori; Michèle Sebag (PKDD, 2004)

Taylor-based pseudo-metrics for random process fitting in dynamic programming: expected loss minimization and risk management. - Sylvain Gelly; Jérémie Mary; Olivier Teytaud (CAP, 2005)

Learning for stochastic dynamic programming. - Sylvain Gelly; Jérémie Mary; Olivier Teytaud (ESANN, 2006)

On the Ultimate Convergence Rates for Isotropic Algorithms and the Best Choices Among Various Forms of Isotropy. - Olivier Teytaud; Sylvain Gelly; Jérémie Mary (PPSN, 2006)

Active learning in regression, with application to stochastic dynamic programming. - Olivier Teytaud; Sylvain Gelly; Jérémie Mary (ICINCO-ICSO, 2007)

Adaptive play in Texas Hold'em Poker. - Raphaël Maîtrepierre; Jérémie Mary; Rémi Munos (ECAI, 2008)

Affichage de publicités sur des portails web. - Victor Gabillon; Jérémie Mary; Philippe Preux (EGC, 2010)

Advertising Campaigns Management: Should We Be Greedy? - Sertan Girgin; Jérémie Mary; Philippe Preux; Olivier Nicol (ICDM, 2010)

Reducing statistical time-series problems to binary classification. - Daniil Ryabko; Jérémie Mary (NIPS, 2012)

Managing advertising campaigns - an approximate planning approach. - Sertan Girgin; Jérémie Mary; Philippe Preux; Olivier Nicol (Frontiers Comput. Sci., 2012)

Online Clustering of Processes. - Azadeh Khaleghi; Daniil Ryabko; Jérémie Mary; Philippe Preux (AISTATS, 2012)

ICML Exploration & Exploitation Challenge: Keep it simple! - Olivier Nicol; Jérémie Mary; Philippe Preux (ICML On-line Trading of Exploration and Exploitation, 2012)

A binary-classification-based metric between time-series distributions and its use in statistical and learning problems. - Daniil Ryabko; Jérémie Mary (J. Mach. Learn. Res., 2013)

Improving offline evaluation of contextual bandit algorithms via bootstrapping techniques. - Jérémie Mary; Philippe Preux; Olivier Nicol (ICML, 2014)

Bandits Warm-up Cold Recommender Systems. - Jérémie Mary; Romaric Gaudel; Philippe Preux (CoRR, 2014)

Cold-start Problems in Recommendation Systems via Contextual-bandit Algorithms. - Hai Thanh Nguyen 001; Jérémie Mary; Philippe Preux (CoRR, 2014)

Data-Driven Recommender Systems: Sequences of recommendations. - Jérémie Mary (2015)

Bandits and Recommender Systems. - Jérémie Mary; Romaric Gaudel; Philippe Preux (MOD, 2015)

Hybrid Recommender System based on Autoencoders. - Florian Strub; Romaric Gaudel; Jérémie Mary (DLRS@RecSys, 2016)

Hybrid Collaborative Filtering with Neural Networks. - Florian Strub; Jérémie Mary; Romaric Gaudel (CoRR, 2016)

Consistent Algorithms for Clustering Time Series. - Azadeh Khaleghi; Daniil Ryabko; Jérémie Mary; Philippe Preux (J. Mach. Learn. Res., 2016)

Parallel Higher Order Alternating Least Square for Tensor Recommender System. - Romain Warlop; Alessandro Lazaric; Jérémie Mary (AAAI Workshops, 2017)

End-to-end optimization of goal-driven and visually grounded dialogue systems. - Florian Strub; Harm de Vries; Jérémie Mary; Bilal Piot; Aaron C. Courville; Olivier Pietquin (IJCAI, 2017)

Modulating early visual processing by language. - Harm de Vries; Florian Strub; Jérémie Mary; Hugo Larochelle; Olivier Pietquin; Aaron C. Courville (NIPS, 2017)

Visual Reasoning with Multi-hop Feature Modulation. - Florian Strub; Mathieu Seurin; Ethan Perez; Harm de Vries; Jérémie Mary; Philippe Preux; Aaron C. Courville; Olivier Pietquin (ECCV (5), 2018)

Fighting Boredom in Recommender Systems with Linear Reinforcement Learning. - Romain Warlop; Alessandro Lazaric; Jérémie Mary (NeurIPS, 2018)

Basket Completion with Multi-task Determinantal Point Processes. - Romain Warlop; Jérémie Mary; Mike Gartrell (CoRR, 2018)

Recurrent Neural Networks for Long and Short-Term Sequential Recommendation. - Kiewan Villatel; Elena Smirnova; Jérémie Mary; Philippe Preux (CoRR, 2018)

Fairness-Aware Learning for Continuous Attributes and Treatments. - Jérémie Mary; Clément Calauzènes; Noureddine El Karoui (ICML, 2019)

Tensorized Determinantal Point Processes for Recommendation. - Romain Warlop; Jérémie Mary; Mike Gartrell (KDD, 2019)

Distributionally Robust Reinforcement Learning. - Elena Smirnova; Elvis Dohmatob; Jérémie Mary (CoRR, 2019)

End-to-End Learning of Geometric Deformations of Feature Maps for Virtual Try-On. - Thibaut Issenhuth; Jérémie Mary; Clément Calauzènes (CoRR, 2019)

Do Not Mask What You Do Not Need to Mask: A Parser-Free Virtual Try-On. - Thibaut Issenhuth; Jérémie Mary; Clément Calauzènes (ECCV (20), 2020)

Learning disconnected manifolds: a no GAN's land. - Ugo Tanielian; Thibaut Issenhuth; Elvis Dohmatob; Jérémie Mary (ICML, 2020)

Learning disconnected manifolds: a no GANs land. - Ugo Tanielian; Thibaut Issenhuth; Elvis Dohmatob; Jérémie Mary (CoRR, 2020)

Latent reweighting, an almost free improvement for GANs. - Thibaut Issenhuth; Ugo Tanielian; David Picard; Jérémie Mary (WACV, 2022)

Lessons from the AdKDD'21 Privacy-Preserving ML Challenge. - Eustache Diemert; Romain Fabre; Alexandre Gilotte; Fei Jia; Basile Leparmentier; Jérémie Mary; Zhonghua Qu; Ugo Tanielian; Hui Yang (WWW, 2022)

Optimal precision for GANs. - Thibaut Issenhuth; Ugo Tanielian; Jérémie Mary; David Picard (CoRR, 2022)

Unveiling the Latent Space Geometry of Push-Forward Generative Models. - Thibaut Issenhuth; Ugo Tanielian; Jérémie Mary; David Picard (ICML, 2023)

Weakly-Supervised Conditional Embedding for Referred Visual Search. - Simon Lepage; Jérémie Mary; David Picard (CoRR, 2023)

EvE: Exploiting Generative Priors for Radiance Field Enrichment. - Karim Kassab; Antoine Schnepf; Jean-Yves Franceschi; Laurent Caraffa; Jérémie Mary; Valérie Gouet-Brunet (CoRR, 2023)

EdiBERT: a generative model for image editing. - Thibaut Issenhuth; Ugo Tanielian; Jérémie Mary; David Picard (Trans. Mach. Learn. Res., 2023)

Exploring 3D-aware Latent Spaces for Efficiently Learning Numerous Scenes. - Antoine Schnepf; Karim Kassab; Jean-Yves Franceschi; Laurent Caraffa; Flavian Vasile; Jérémie Mary; Andrew I. Comport; Valérie Gouet-Brunet (CoRR, 2024)

Scaled Inverse Graphics: Efficiently Learning Large Sets of 3D Scenes. - Karim Kassab; Antoine Schnepf; Jean-Yves Franceschi; Laurent Caraffa; Flavian Vasile; Jérémie Mary; Andrew I. Comport; Valérie Gouet-Brunet (CoRR, 2024)

Bringing NeRFs to the Latent Space: Inverse Graphics Autoencoder. - Antoine Schnepf; Karim Kassab; Jean-Yves Franceschi; Laurent Caraffa; Flavian Vasile; Jérémie Mary; Andrew I. Comport; Valérie Gouet-Brunet (ICLR, 2025)

RefinedFields: Radiance Fields Refinement for Planar Scene Representations. - Karim Kassab; Antoine Schnepf; Jean-Yves Franceschi; Laurent Caraffa; Jérémie Mary; Valérie Gouet-Brunet (Trans. Mach. Learn. Res., 2025)