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09/08/2023
Modeling Recommender Ecosystems: Research Challenges at the Intersection of Mechanism Design, Reinforcement Learning and Generative Models
Modern recommender systems lie at the heart of complex ecosystems that c...
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09/02/2023
Content Prompting: Modeling Content Provider Dynamics to Improve User Welfare in Recommender Ecosystems
Users derive value from a recommender system (RS) only to the extent tha...
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05/24/2023
Ranking with Popularity Bias: User Welfare under Self-Amplification Dynamics
While popularity bias is recognized to play a role in recommmender (and ...
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02/04/2023
Reinforcement Learning with History-Dependent Dynamic Contexts
We introduce Dynamic Contextual Markov Decision Processes (DCMDPs), a no...
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03/14/2021
RecSim NG: Toward Principled Uncertainty Modeling for Recommender Ecosystems
The development of recommender systems that optimize multi-turn interact...
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02/11/2021
Meta-Thompson Sampling
Efficient exploration in multi-armed bandits is a fundamental online lea...
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07/31/2020
Optimizing Long-term Social Welfare in Recommender Systems: A Constrained Matching Approach
Most recommender systems (RS) research assumes that a user's utility can...
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06/09/2020
Differentiable Meta-Learning in Contextual Bandits
We study a contextual bandit setting where the learning agent has access...
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02/17/2020
Differentiable Bandit Exploration
We learn bandit policies that maximize the average reward over bandit in...
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09/11/2019
RecSim: A Configurable Simulation Platform for Recommender Systems
We propose RecSim, a configurable platform for authoring simulation envi...
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05/29/2019
Advantage Amplification in Slowly Evolving Latent-State Environments
Latent-state environments with long horizons, such as those faced by rec...
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04/04/2019
Empirical Bayes Regret Minimization
The prevalent approach to bandit algorithm design is to have a low-regre...
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05/07/2018
Planning and Learning with Stochastic Action Sets
In many practical uses of reinforcement learning (RL) the set of actions...
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06/14/2016
Lifted Convex Quadratic Programming
Symmetry is the essential element of lifted inference that has recently ...
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05/26/2016
The Symbolic Interior Point Method
A recent trend in probabilistic inference emphasizes the codification of...
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10/12/2014