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2020 – today
- 2024
[c26]Olivier Jeunen
, Harrie Oosterhuis, Yuta Saito, Flavian Vasile, Yixin Wang:
CONSEQUENCES - The 3rd Workshop on Causality, Counterfactuals and Sequential Decision-Making for Recommender Systems. RecSys 2024: 1206-1209- [i28]Antoine Schnepf, Karim Kassab, Jean-Yves Franceschi, Laurent Caraffa, Flavian Vasile, Jérémie Mary, Andrew Comport, Valérie Gouet-Brunet:
Exploring 3D-aware Latent Spaces for Efficiently Learning Numerous Scenes. CoRR abs/2403.11678 (2024) - 2023
- [c25]Olivier Jeunen, Thorsten Joachims, Harrie Oosterhuis, Yuta Saito, Flavian Vasile, Yixin Wang:
CONSEQUENCES - The 2nd Workshop on Causality, Counterfactuals and Sequential Decision-Making for Recommender Systems. RecSys 2023: 1223-1226 - [i27]Veronika Shilova, Ludovic Dos Santos, Flavian Vasile, Gaëtan Racic, Ugo Tanielian:
AdBooster: Personalized Ad Creative Generation using Stable Diffusion Outpainting. CoRR abs/2309.11507 (2023) - [i26]Antoine Schnepf, Flavian Vasile, Ugo Tanielian:
3DGEN: A GAN-based approach for generating novel 3D models from image data. CoRR abs/2312.08094 (2023) - 2022
- [c24]Imad Aouali, Amine Benhalloum, Martin Bompaire, Achraf Ait Sidi Hammou, Sergey Ivanov, Benjamin Heymann, David Rohde, Otmane Sakhi, Flavian Vasile, Maxime Vono:
Reward Optimizing Recommendation using Deep Learning and Fast Maximum Inner Product Search. KDD 2022: 4772-4773 - [c23]Olivier Jeunen, Thorsten Joachims, Harrie Oosterhuis, Yuta Saito, Flavian Vasile:
CONSEQUENCES - Causality, Counterfactuals and Sequential Decision-Making for Recommender Systems. RecSys 2022: 654-657 - [i25]Benjamin Heymann, Flavian Vasile, David Rohde:
Welfare-Optimized Recommender Systems. CoRR abs/2206.13845 (2022) - [i24]Imad Aouali, Achraf Ait Sidi Hammou, Sergey Ivanov, Otmane Sakhi, David Rohde, Flavian Vasile:
A Scalable Probabilistic Model for Reward Optimizing Slate Recommendation. CoRR abs/2208.06263 (2022) - [i23]Imad Aouali, Amine Benhalloum, Martin Bompaire, Benjamin Heymann, Olivier Jeunen, David Rohde, Otmane Sakhi, Flavian Vasile:
Offline Evaluation of Reward-Optimizing Recommender Systems: The Case of Simulation. CoRR abs/2209.08642 (2022) - 2021
- [i22]Imad Aouali, Sergey Ivanov, Mike Gartrell, David Rohde, Flavian Vasile, Victor Zaytsev, Diego Legrand:
Combining Reward and Rank Signals for Slate Recommendation. CoRR abs/2107.12455 (2021) - 2020
- [c22]Louis Faury, Ugo Tanielian, Elvis Dohmatob, Elena Smirnova, Flavian Vasile:
Distributionally Robust Counterfactual Risk Minimization. AAAI 2020: 3850-3857 - [c21]Otmane Sakhi, Stephen Bonner, David Rohde, Flavian Vasile:
BLOB: A Probabilistic Model for Recommendation that Combines Organic and Bandit Signals. KDD 2020: 783-793 - [c20]Olivier Jeunen, David Rohde, Flavian Vasile, Martin Bompaire:
Joint Policy-Value Learning for Recommendation. KDD 2020: 1223-1233 - [c19]Thorsten Joachims, Yves Raimond, Olivier Koch, Maria Dimakopoulou, Flavian Vasile, Adith Swaminathan:
REVEAL 2020: Bandit and Reinforcement Learning from User Interactions. RecSys 2020: 628-629 - [c18]David Rohde, Flavian Vasile, Sergey Ivanov, Otmane Sakhi:
Bayesian Value Based Recommendation: A modelling based alternative to proxy and counterfactual policy based recommendation. RecSys 2020: 742-744 - [c17]Flavian Vasile, David Rohde, Olivier Jeunen, Amine Benhalloum:
A Gentle Introduction to Recommendation as Counterfactual Policy Learning. UMAP 2020: 392-393 - [i21]Otmane Sakhi, Stephen Bonner, David Rohde, Flavian Vasile:
BLOB : A Probabilistic Model for Recommendation that Combines Organic and Bandit Signals. CoRR abs/2008.12504 (2020) - [i20]Philomène Chagniot, Flavian Vasile, David Rohde:
From Clicks to Conversions: Recommendation for long-term reward. CoRR abs/2009.00497 (2020) - [i19]Otmane Sakhi, Louis Faury, Flavian Vasile:
Improving Offline Contextual Bandits with Distributional Robustness. CoRR abs/2011.06835 (2020)
2010 – 2019
- 2019
- [c16]Flavian Vasile, Stephen Bonner:
Causal Embeddings for Recommendation: An Extended Abstract. IJCAI 2019: 6236-6240 - [c15]Ugo Tanielian, Flavian Vasile:
Relaxed softmax for PU learning. RecSys 2019: 119-127 - [c14]Thorsten Joachims, Maria Dimakopoulou, Adith Swaminathan, Yves Raimond, Olivier Koch, Flavian Vasile:
REVEAL 2019: closing the loop with the real world: reinforcement and robust estimators for recommendation. RecSys 2019: 568-569 - [i18]Stephen Bonner, Flavian Vasile:
Causal Embeddings for Recommendation: An Extended Abstract. CoRR abs/1904.05165 (2019) - [i17]Dmytro Mykhaylov, David Rohde, Flavian Vasile:
Three Methods for Training on Bandit Feedback. CoRR abs/1904.10799 (2019) - [i16]Louis Faury, Ugo Tanielian, Flavian Vasile, Elena Smirnova, Elvis Dohmatob:
Distributionally Robust Counterfactual Risk Minimization. CoRR abs/1906.06211 (2019) - [i15]Olivier Jeunen, David Rohde, Flavian Vasile:
On the Value of Bandit Feedback for Offline Recommender System Evaluation. CoRR abs/1907.12384 (2019) - [i14]Nhan Nguyen-Thanh, Dana Marinca, Kinda Khawam, David Rohde, Flavian Vasile, Elena Simona Lohan, Steven Martin, Dominique Quadri:
Recommendation System-based Upper Confidence Bound for Online Advertising. CoRR abs/1909.04190 (2019) - [i13]Ugo Tanielian, Flavian Vasile:
Relaxed Softmax for learning from Positive and Unlabeled data. CoRR abs/1909.08079 (2019) - [i12]Olivier Jeunen, Dmytro Mykhaylov, David Rohde, Flavian Vasile, Alexandre Gilotte, Martin Bompaire:
Learning from Bandit Feedback: An Overview of the State-of-the-art. CoRR abs/1909.08471 (2019) - [i11]Otmane Sakhi, Stephen Bonner, David Rohde, Flavian Vasile:
Reconsidering Analytical Variational Bounds for Output Layers of Deep Networks. CoRR abs/1910.00877 (2019) - 2018
- [c13]Louis Faury, Flavian Vasile:
Rover Descent: Learning to Optimize by Learning to Navigate on Prototypical Loss Surfaces. LION 2018: 271-287 - [c12]Stephen Bonner, Flavian Vasile:
Causal embeddings for recommendation. RecSys 2018: 104-112 - [c11]Balázs Hidasi, Alexandros Karatzoglou, Oren Sar Shalom, Bracha Shapira, Domonkos Tikk, Flavian Vasile, Sander Dieleman:
DLRS 2018: third workshop on deep learning for recommender systems. RecSys 2018: 512-513 - [c10]Thorsten Joachims, Adith Swaminathan, Yves Raimond, Olivier Koch, Flavian Vasile:
REVEAL 2018: offline evaluation for recommender systems. RecSys 2018: 514-515 - [c9]Ugo Tanielian, Anne-Marie Tousch, Flavian Vasile:
Siamese Cookie Embedding Networks for Cross-Device User Matching. WWW (Companion Volume) 2018: 85-86 - [e1]Balázs Hidasi, Alexandros Karatzoglou, Oren Sar Shalom, Bracha Shapira, Domonkos Tikk, Flavian Vasile, Sander Dieleman:
Proceedings of the 3rd Workshop on Deep Learning for Recommender Systems, DLRS@RecSys 2018, Vancouver, BC, Canada, October 6, 2018. ACM 2018, ISBN 978-1-4503-6617-5 [contents] - [i10]Louis Faury, Flavian Vasile:
Rover Descent: Learning to optimize by learning to navigate on prototypical loss surfaces. CoRR abs/1801.07222 (2018) - [i9]Ugo Tanielian, Anne-Marie Tousch, Flavian Vasile:
Siamese Cookie Embedding Networks for Cross-Device User Matching. CoRR abs/1803.10450 (2018) - [i8]Louis Faury, Flavian Vasile, Clément Calauzènes, Olivier Fercoq:
Neural Generative Models for Global Optimization with Gradients. CoRR abs/1805.08594 (2018) - [i7]Ugo Tanielian, Mike Gartrell, Flavian Vasile:
Adversarial Training of Word2Vec for Basket Completion. CoRR abs/1805.08720 (2018) - [i6]David Rohde, Stephen Bonner, Travis Dunlop, Flavian Vasile, Alexandros Karatzoglou:
RecoGym: A Reinforcement Learning Environment for the problem of Product Recommendation in Online Advertising. CoRR abs/1808.00720 (2018) - 2017
- [c8]Flavian Vasile, Damien Lefortier, Olivier Chapelle:
Cost-sensitive Learning for Utility Optimization in Online Advertising Auctions. ADKDD@KDD 2017: 8:1-8:6 - [c7]Elena Smirnova, Flavian Vasile:
Contextual Sequence Modeling for Recommendation with Recurrent Neural Networks. DLRS@RecSys 2017: 2-9 - [c6]Thomas Nedelec, Elena Smirnova, Flavian Vasile:
Specializing Joint Representations for the task of Product Recommendation. DLRS@RecSys 2017: 10-18 - [i5]Thomas Nedelec, Elena Smirnova, Flavian Vasile:
Specializing Joint Representations for the task of Product Recommendation. CoRR abs/1706.07625 (2017) - [i4]Stephen Bonner, Flavian Vasile:
Causal Embeddings for Recommendation. CoRR abs/1706.07639 (2017) - [i3]Elena Smirnova, Flavian Vasile:
Contextual Sequence Modeling for Recommendation with Recurrent Neural Networks. CoRR abs/1706.07684 (2017) - 2016
- [c5]Flavian Vasile, Elena Smirnova, Alexis Conneau:
Meta-Prod2Vec: Product Embeddings Using Side-Information for Recommendation. RecSys 2016: 225-232 - [i2]Flavian Vasile, Damien Lefortier:
Cost-sensitive Learning for Bidding in Online Advertising Auctions. CoRR abs/1603.03713 (2016) - [i1]Flavian Vasile, Elena Smirnova, Alexis Conneau:
Meta-Prod2Vec - Product Embeddings Using Side-Information for Recommendation. CoRR abs/1607.07326 (2016) - 2010
- [c4]Yiping Zhou, Lan Nie, Omid Rouhani-Kalleh, Flavian Vasile, Scott Gaffney:
Resolving Surface Forms to Wikipedia Topics. COLING 2010: 1335-1343
2000 – 2009
- 2009
- [c3]Andrew Carlson, Scott Gaffney, Flavian Vasile:
Learning a Named Entity Tagger from Gazetteers with the Partial Perceptron. AAAI Spring Symposium: Learning by Reading and Learning to Read 2009: 7-13 - 2007
- [c2]Flavian Vasile, Samik Basu:
Cost-based Analysis of Multiple Counter-Examples. SEKE 2007: 33-38 - 2006
- [c1]Flavian Vasile, Adrian Silvescu, Dae-Ki Kang, Vasant G. Honavar:
TRIPPER: Rule Learning Using Taxonomies. PAKDD 2006: 55-59
Coauthor Index
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last updated on 2024-10-23 21:21 CEST by the dblp team
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