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Martin Mladenov

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Demystifying Embedding Spaces using Large Language Models

Oct 06, 2023
Guy Tennenholtz, Yinlam Chow, Chih-Wei Hsu, Jihwan Jeong, Lior Shani, Azamat Tulepbergenov, Deepak Ramachandran, Martin Mladenov, Craig Boutilier

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Modeling Recommender Ecosystems: Research Challenges at the Intersection of Mechanism Design, Reinforcement Learning and Generative Models

Sep 22, 2023
Craig Boutilier, Martin Mladenov, Guy Tennenholtz

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Content Prompting: Modeling Content Provider Dynamics to Improve User Welfare in Recommender Ecosystems

Sep 02, 2023
Siddharth Prasad, Martin Mladenov, Craig Boutilier

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Reinforcement Learning with History-Dependent Dynamic Contexts

Feb 04, 2023
Guy Tennenholtz, Nadav Merlis, Lior Shani, Martin Mladenov, Craig Boutilier

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Towards Content Provider Aware Recommender Systems: A Simulation Study on the Interplay between User and Provider Utilities

May 06, 2021
Ruohan Zhan, Konstantina Christakopoulou, Ya Le, Jayden Ooi, Martin Mladenov, Alex Beutel, Craig Boutilier, Ed H. Chi, Minmin Chen

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RecSim NG: Toward Principled Uncertainty Modeling for Recommender Ecosystems

Mar 14, 2021
Martin Mladenov, Chih-Wei Hsu, Vihan Jain, Eugene Ie, Christopher Colby, Nicolas Mayoraz, Hubert Pham, Dustin Tran, Ivan Vendrov, Craig Boutilier

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Meta-Thompson Sampling

Feb 11, 2021
Branislav Kveton, Mikhail Konobeev, Manzil Zaheer, Chih-wei Hsu, Martin Mladenov, Craig Boutilier, Csaba Szepesvari

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Optimizing Long-term Social Welfare in Recommender Systems: A Constrained Matching Approach

Aug 18, 2020
Martin Mladenov, Elliot Creager, Omer Ben-Porat, Kevin Swersky, Richard Zemel, Craig Boutilier

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