activity
20182023
most citedRecoGym: A Reinforcement Learning Environment for the problem of Product Recommendation in Online Advertising

60 citations · 107 across the 20 of their papers we have counts for

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Showing 2022Show all

5 papers · 1 filter

cs.LG2022

Learning from aggregated data with a maximum entropy model

Alexandre Gilotte, Ahmed Ben Yahmed, David Rohde

Aggregating a dataset, then injecting some noise, is a simple and common way to release differentially private data.However, aggregated data -- even without noise -- is not an appr…

cs.IR2022★ 1 cited

Offline Evaluation of Reward-Optimizing Recommender Systems: The Case of Simulation

Imad Aouali, Amine Benhalloum, Martin Bompaire +5

Both in academic and industry-based research, online evaluation methods are seen as the golden standard for interactive applications like recommendation systems. Naturally, the rea…

cs.IR2022★ 1 cited

Probabilistic Rank and Reward: A Scalable Model for Slate Recommendation

Imad Aouali, Achraf Ait Sidi Hammou, Otmane Sakhi +2

We introduce Probabilistic Rank and Reward (PRR), a scalable probabilistic model for personalized slate recommendation. Our approach allows off-policy estimation of the reward in t…

cs.IR2022

Fast Offline Policy Optimization for Large Scale Recommendation

Otmane Sakhi, David Rohde, Alexandre Gilotte

Personalised interactive systems such as recommender systems require selecting relevant items from massive catalogs dependent on context. Reward-driven offline optimisation of thes…

cs.GT2022

Welfare-Optimized Recommender Systems

Benjamin Heymann, Flavian Vasile, David Rohde

We present a recommender system based on the Random Utility Model. Online shoppers are modeled as rational decision makers with limited information, and the recommendation task is…