1 citations · 1 across the 5 of their papers we have counts for
5 papers
Off-Policy Evaluation for Semantic ID Recommenders: Does the Model's Own Code Hierarchy Help?
Artem Betlei
Generative recommenders increasingly emit semantic IDs (SIDs): each item is a short sequence of hierarchical discrete codes from a residual quantizer, decoded autoregressively. Bef…
Abacus: Self-Supervised Event Counting-Aligned Distributional Pretraining for Sequential User Modeling
Sullivan Castro, Artem Betlei, Thomas Di Martino +1
Modeling user purchase behavior is a critical challenge in display advertising systems, necessary for real-time bidding. The difficulty arises from the sparsity of positive user ev…
Maximizing the Success Probability of Policy Allocations in Online Systems
Artem Betlei, Mariia Vladimirova, Mehdi Sebbar +3
The effectiveness of advertising in e-commerce largely depends on the ability of merchants to bid on and win impressions for their targeted users. The bidding procedure is highly c…
A Large Scale Benchmark for Individual Treatment Effect Prediction and Uplift Modeling
Eustache Diemert, Artem Betlei, Christophe Renaudin +3
Individual Treatment Effect (ITE) prediction is an important area of research in machine learning which aims at explaining and estimating the causal impact of an action at the gran…
Treatment Targeting by AUUC Maximization with Generalization Guarantees
Artem Betlei, Eustache Diemert, Massih-Reza Amini
We consider the task of optimizing treatment assignment based on individual treatment effect prediction. This task is found in many applications such as personalized medicine or ta…