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ORCIDOlivier Jeunen
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2020 – today
- 2024
[c29]Shubham Baweja, Neeti Pokharna, Aleksei Ustimenko, Olivier Jeunen:
Variance Reduction in Ratio Metrics for Efficient Online Experiments. ECIR (5) 2024: 292-297- [c28]Hitesh Sagtani
, Olivier Jeunen, Aleksei Ustimenko:
Learning-to-Rank with Nested Feedback. ECIR (3) 2024: 306-315 - [c27]Olivier Jeunen, Ivan Potapov, Aleksei Ustimenko:
On (Normalised) Discounted Cumulative Gain as an Off-Policy Evaluation Metric for Top-n Recommendation. KDD 2024: 1222-1233 - [c26]Olivier Jeunen, Aleksei Ustimenko:
Learning Metrics that Maximise Power for Accelerated A/B-Tests. KDD 2024: 5183-5193 - [c25]Olivier Jeunen, Jatin Mandav, Ivan Potapov, Nakul Agarwal, Sourabh Vaid, Wenzhe Shi, Aleksei Ustimenko:
Multi-Objective Recommendation via Multivariate Policy Learning. RecSys 2024: 712-721 - [c24]Shashank Gupta, Olivier Jeunen, Harrie Oosterhuis, Maarten de Rijke:
Optimal Baseline Corrections for Off-Policy Contextual Bandits. RecSys 2024: 722-732 - [c23]Olivier Jeunen, Shubham Baweja, Neeti Pokharna, Aleksei Ustimenko:
Powerful A/B-Testing Metrics and Where to Find Them. RecSys 2024: 816-818 - [c22]Olivier Jeunen, Aleksei Ustimenko:
Δ-OPE: Off-Policy Estimation with Pairs of Policies. RecSys 2024: 878-883 - [c21]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 - [c20]Srijan Saket, Olivier Jeunen, Md. Danish Kalim:
Monitoring the Evolution of Behavioural Embeddings in Social Media Recommendation. SIGIR 2024: 2935-2939 - [c19]Hitesh Sagtani, Madan Gopal Jhawar, Rishabh Mehrotra, Olivier Jeunen:
Ad-load Balancing via Off-policy Learning in a Content Marketplace. WSDM 2024: 586-595 - [c18]Bram van den Akker, Olivier Jeunen, Ying Li, Ben London, Zahra Nazari, Devesh Parekh:
Practical Bandits: An Industry Perspective. WSDM 2024: 1132-1135 - [i20]Hitesh Sagtani, Olivier Jeunen, Aleksei Ustimenko:
Learning-to-Rank with Nested Feedback. CoRR abs/2401.04053 (2024) - [i19]Shubham Baweja, Neeti Pokharna, Aleksei Ustimenko, Olivier Jeunen:
Variance Reduction in Ratio Metrics for Efficient Online Experiments. CoRR abs/2401.04062 (2024) - [i18]Olivier Jeunen, Aleksei Ustimenko:
Learning Metrics that Maximise Power for Accelerated A/B-Tests. CoRR abs/2402.03915 (2024) - [i17]Olivier Jeunen, Jatin Mandav, Ivan Potapov, Nakul Agarwal, Sourabh Vaid, Wenzhe Shi, Aleksei Ustimenko:
Multi-Objective Recommendation via Multivariate Policy Learning. CoRR abs/2405.02141 (2024) - [i16]Shashank Gupta, Olivier Jeunen, Harrie Oosterhuis, Maarten de Rijke:
Optimal Baseline Corrections for Off-Policy Contextual Bandits. CoRR abs/2405.05736 (2024) - [i15]Olivier Jeunen, Aleksei Ustimenko:
Δ-OPE: Off-Policy Estimation with Pairs of Policies. CoRR abs/2405.10024 (2024) - [i14]Olivier Jeunen, Shubham Baweja, Neeti Pokharna, Aleksei Ustimenko:
Powerful A/B-Testing Metrics and Where to Find Them. CoRR abs/2407.20665 (2024) - [i13]Olivier Jeunen:
A Simple Model to Estimate Sharing Effects in Social Networks. CoRR abs/2409.12203 (2024) - 2023
- [j3]Olivier Jeunen:
A Common Misassumption in Online Experiments with Machine Learning Models. SIGIR Forum 57(1): 13:1-13:9 (2023) - [j2]Olivier Jeunen, Bart Goethals:
Pessimistic Decision-Making for Recommender Systems. Trans. Recomm. Syst. 1(1): 1-27 (2023) - [c17]Olivier Jeunen, Hitesh Sagtani, Himanshu Doi, Rasul Karimov, Neeti Pokharna, Md. Danish Kalim, Aleksei Ustimenko, Christopher Green, Rishabh Mehrotra, Wenzhe Shi:
On Gradient Boosted Decision Trees and Neural Rankers: A Case-Study on Short-Video Recommendations at ShareChat. FIRE 2023: 136-141 - [c16]Olivier Jeunen, Sean Murphy, Ben Allison:
Off-Policy Learning-to-Bid with AuctionGym. KDD 2023: 4219-4228 - [c15]Olivier Jeunen:
Abstract: A Common Misassumption in Online Experiments with Machine Learning Models. Perspectives@RecSys 2023 - [c14]Olivier Jeunen:
A Probabilistic Position Bias Model for Short-Video Recommendation Feeds. RecSys 2023: 675-681 - [c13]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 - [c12]Valeria Fionda, Olaf Hartig, Reyhaneh Abdolazimi, Sihem Amer-Yahia, Hongzhi Chen, Xiao Chen, Peng Cui, Jeffrey Dalton, Xin Luna Dong, Lisette Espín-Noboa, Wenqi Fan, Manuela Fritz, Quan Gan, Jingtong Gao, Xiaojie Guo, Torsten Hahmann, Jiawei Han, Soyeon Caren Han, Estevam Hruschka, Liang Hu, Jiaxin Huang, Utkarshani Jaimini, Olivier Jeunen, Yushan Jiang, Fariba Karimi, George Karypis, Krishnaram Kenthapadi, Himabindu Lakkaraju, Hady W. Lauw, Thai Le, Trung-Hoang Le, Dongwon Lee, Geon Lee, Liat Levontin, Cheng-Te Li, Haoyang Li, Ying Li, Jay Chiehen Liao, Qidong Liu, Usha Lokala, Ben London, Siqu Long, Hande Küçük-McGinty, Yu Meng, Seungwhan Moon, Usman Naseem, Pradeep Natarajan, Behrooz Omidvar-Tehrani, Zijie Pan, Devesh Parekh, Jian Pei, Tiago Peixoto, Steven Pemberton, Josiah Poon, Filip Radlinski, Federico Rossetto, Kaushik Roy, Aghiles Salah, Mehrnoosh Sameki, Amit P. Sheth, Cogan Shimizu, Kijung Shin, Dongjin Song, Julia Stoyanovich, Dacheng Tao, Johanne Trippas, Quoc Truong, Yu-Che Tsai, Adaku Uchendu, Bram van den Akker, Lin Wang, Minjie Wang, Shoujin Wang, Xin Wang, Ingmar Weber, Henry Weld, Lingfei Wu, Da Xu, Yifan Ethan Xu, Shuyuan Xu, Bo Yang, Ke Yang, Elad Yom-Tov, Jaemin Yoo, Zhou Yu, Reza Zafarani, Hamed Zamani, Meike Zehlike, Qi Zhang, Xikun Zhang, Yongfeng Zhang, Yu Zhang, Zheng Zhang, Liang Zhao, Xiangyu Zhao, Wenwu Zhu:
Tutorials at The Web Conference 2023. WWW (Companion Volume) 2023: 648-658 - [i12]Bram van den Akker, Olivier Jeunen, Ying Li, Ben London, Zahra Nazari, Devesh Parekh:
Practical Bandits: An Industry Perspective. CoRR abs/2302.01223 (2023) - [i11]Olivier Jeunen:
A Common Misassumption in Online Experiments with Machine Learning Models. CoRR abs/2304.10900 (2023) - [i10]Gabriel Bénédict, Olivier Jeunen, Samuele Papa, Samarth Bhargav, Daan Odijk, Maarten de Rijke:
RecFusion: A Binomial Diffusion Process for 1D Data for Recommendation. CoRR abs/2306.08947 (2023) - [i9]Olivier Jeunen:
A Probabilistic Position Bias Model for Short-Video Recommendation Feeds. CoRR abs/2307.14059 (2023) - [i8]Olivier Jeunen, Ivan Potapov, Aleksei Ustimenko:
On (Normalised) Discounted Cumulative Gain as an Offline Evaluation Metric for Top-n Recommendation. CoRR abs/2307.15053 (2023) - [i7]Olivier Jeunen, Ben London:
Offline Recommender System Evaluation under Unobserved Confounding. CoRR abs/2309.04222 (2023) - [i6]Hitesh Sagtani, Madan Gopal Jhawar, Rishabh Mehrotra, Olivier Jeunen:
Ad-load Balancing via Off-policy Learning in a Content Marketplace. CoRR abs/2309.11518 (2023) - [i5]Olivier Jeunen, Hitesh Sagtani, Himanshu Doi, Rasul Karimov, Neeti Pokharna, Md. Danish Kalim, Aleksei Ustimenko, Christopher Green, Wenzhe Shi, Rishabh Mehrotra:
On Gradient Boosted Decision Trees and Neural Rankers: A Case-Study on Short-Video Recommendations at ShareChat. CoRR abs/2312.01760 (2023) - 2022
- [j1]Olivier Jeunen, Jan Van Balen, Bart Goethals:
Embarrassingly shallow auto-encoders for dynamic collaborative filtering. User Model. User Adapt. Interact. 32(4): 509-541 (2022) - [c11]Olivier Jeunen, Ciarán M. Gilligan-Lee, Rishabh Mehrotra, Mounia Lalmas:
Disentangling Causal Effects from Sets of Interventions in the Presence of Unobserved Confounders. NeurIPS 2022 - [c10]Olivier Jeunen, Thorsten Joachims, Harrie Oosterhuis, Yuta Saito, Flavian Vasile:
CONSEQUENCES - Causality, Counterfactuals and Sequential Decision-Making for Recommender Systems. RecSys 2022: 654-657 - [i4]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) - [i3]Olivier Jeunen, Ciarán M. Gilligan-Lee, Rishabh Mehrotra, Mounia Lalmas:
Disentangling Causal Effects from Sets of Interventions in the Presence of Unobserved Confounders. CoRR abs/2210.05446 (2022) - 2021
- [b1]Olivier Jeunen:
Offline approaches to recommendation with online success. University of Antwerp, Belgium, 2021 - [c9]Olivier Jeunen, Bart Goethals:
Pessimistic Reward Models for Off-Policy Learning in Recommendation. RecSys 2021: 63-74 - [c8]Olivier Jeunen, Bart Goethals:
Top-K Contextual Bandits with Equity of Exposure. RecSys 2021: 310-320 - 2020
- [c7]Olivier Jeunen, David Rohde, Flavian Vasile, Martin Bompaire:
Joint Policy-Value Learning for Recommendation. KDD 2020: 1223-1233 - [c6]Olivier Jeunen, Jan Van Balen, Bart Goethals:
Closed-Form Models for Collaborative Filtering with Side-Information. RecSys 2020: 651-656 - [c5]Flavian Vasile, David Rohde, Olivier Jeunen, Amine Benhalloum:
A Gentle Introduction to Recommendation as Counterfactual Policy Learning. UMAP 2020: 392-393
2010 – 2019
- 2019
- [c4]Olivier Jeunen, Koen Verstrepen, Bart Goethals:
Efficient similarity computation for collaborative filtering in dynamic environments. RecSys 2019: 251-259 - [c3]Sandy Moens, Olivier Jeunen, Bart Goethals:
Interactive evaluation of recommender systems with SNIPER: an episode mining approach. RecSys 2019: 538-539 - [c2]Olivier Jeunen:
Revisiting offline evaluation for implicit-feedback recommender systems. RecSys 2019: 596-600 - [i2]Olivier Jeunen, David Rohde, Flavian Vasile:
On the Value of Bandit Feedback for Offline Recommender System Evaluation. CoRR abs/1907.12384 (2019) - [i1]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) - 2018
- [c1]Olivier Jeunen, Patrick Bosch, Michiel Van Herwegen, Karel Van Doorselaer, Nick Godman, Steven Latré:
A Machine Learning Approach for IEEE 802.11 Channel Allocation. CNSM 2018: 28-36
Coauthor Index
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last updated on 2024-10-23 21:24 CEST by the dblp team
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