Proceedings
The poster session will be run on gather.town. The id of the poster in gather.town corresponds to the id of the paper in the list below.
A Distributed Asynchronous Deep Reinforcement Learning Framework for Recommender Systems [PDF] // Bichen Shi (UCD); Elias Z Tragos (UCD); Makbule Gulcin Ozsoy (UCD); Ruihai Dong (UCD); Barry Smyth (Insight Centre for Data Analytics); Neil Joseph Hurley (University College Dublin); Aonghus Lawlor (UCD) [poster]
A Hybrid Learning-Based Model for Wine Recommendation [PDF] // Chayma Sellami (LIAS/ENSMA); Mounir Bechchi (O°code); Stephane Jean (ensma); hadjali allel (ensma); Mickael Baron (ensma); Dominique Chabot (O°code) [poster]
A Large-scale Open Dataset for Bandit Algorithms [PDF] // Yuta Saito (Tokyo Institute of Technology); Shunsuke Aihara (ZOZO Technologies, Inc.); Megumi Matsutani (ZOZO Research); Yusuke Narita (Yale University) [poster]
A multi stakeholder multi armed bandit news recommender [PDF] // Céderique Vermeersch (KU Leuven); Céderique Vermeersch (KU Leuven) [poster]
An Empirical Evaluation of Doubly Robust Learning for Recommendation [PDF] // Olivier Jeunen (University of Antwerp); Bart Goethals (Universiteit Antwerpen) [poster]
Data-Driven Off-Policy Estimator Selection: An Application in User Marketing on An Online Content Delivery Service [PDF] // Yuta Saito (Tokyo Institute of Technology); Takuma Udagawa (Sony Corporation); Kei Tateno (Sony Corporation) [poster]
Dirichlet-Luce Choice Model for Learning from Interactions [PDF] // Gokhan Capan (Bogazici University); Ilker Gundogdu (Bogazici University); Ali Caner Türkmen (Amazon Research); Ali Taylan Cemgil (DeepMind) [poster]
Exploration in Two-Stage Recommender Systems [PDF] // Jiri Hron (University of Cambridge); Karl Krauth (UC Berkeley); Michael Jordan (UC Berkeley); Niki Kilbertus (Max Planck Institute for Intelligent Systems) [poster]
From Clicks to Conversions: Recommendation for long-term reward [PDF] // Chagniot Philomène (ENS Paris Saclay, Criteo); Flavian Vasile (Criteo); David J. Rohde (Criteo) [poster]
Improving Offline Contextual Bandits with Distributional Robustness [PDF] // Otmane Sakhi (Criteo); Louis Faury (Criteo AI Lab); Flavian Vasile (Criteo) [poster]
Multinomial Logit Learning to Rank [PDF] // James A Grant (Lancaster University); David S Leslie (Lancaster University) [poster]
Odds-Ratio Thompson Sampling to Adjust for Batch Effect [PDF] // Sulgi Kim (NAVER Corp.); Kyung-Min Kim (Clova AI Research, NAVER Corp.) [poster]
Offline Policy Evaluation with Partial Feedback [PDF] // Hongliang Yu (eBay Inc); Xin Yin (eBay Inc); Chieh Lo (eBay Inc); Adam Ilardi (eBay Inc); Sriganesh Madhvanath (eBay Inc) [poster]
Relational Contextual Bandits [PDF] // Ashutosh Dilipbhai Kakadiya (Indian Institute of Technology, Madras) [poster]
A Decision Theoretic Framework for Recommender Systems Approaches // David J. Rohde (Criteo); Otmane Sakhi (Criteo); Flavian Vasile (Criteo) [poster]