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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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06/02/2023
A Convex Relaxation Approach to Bayesian Regret Minimization in Offline Bandits
Algorithms for offline bandits must optimize decisions in uncertain envi...
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06/01/2023
Delphic Offline Reinforcement Learning under Nonidentifiable Hidden Confounding
A prominent challenge of offline reinforcement learning (RL) is the issu...
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05/31/2023
Representation-Driven Reinforcement Learning
We present a representation-driven framework for reinforcement learning....
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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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05/30/2022
Reinforcement Learning with a Terminator
We present the problem of reinforcement learning with exogenous terminat...
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10/13/2021
On Covariate Shift of Latent Confounders in Imitation and Reinforcement Learning
We consider the problem of using expert data with unobserved confounders...
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09/22/2021
Locality Matters: A Scalable Value Decomposition Approach for Cooperative Multi-Agent Reinforcement Learning
Cooperative multi-agent reinforcement learning (MARL) faces significant ...
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03/18/2021
Maximum Entropy Reinforcement Learning with Mixture Policies
Mixture models are an expressive hypothesis class that can approximate a...
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02/22/2021
Action Redundancy in Reinforcement Learning
Maximum Entropy (MaxEnt) reinforcement learning is a powerful learning p...
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02/22/2021
GELATO: Geometrically Enriched Latent Model for Offline Reinforcement Learning
Offline reinforcement learning approaches can generally be divided to pr...
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07/26/2020
The Pendulum Arrangement: Maximizing the Escape Time of Heterogeneous Random Walks
We identify a fundamental phenomenon of heterogeneous one dimensional ra...
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06/11/2020
Bandits with Partially Observable Offline Data
We study linear contextual bandits with access to a large, partially obs...
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10/02/2019
Natural Language State Representation for Reinforcement Learning
Recent advances in Reinforcement Learning have highlighted the difficult...
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09/09/2019
Off-Policy Evaluation in Partially Observable Environments
This work studies the problem of batch off-policy evaluation for Reinfor...
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05/23/2019
Distributional Policy Optimization: An Alternative Approach for Continuous Control
We identify a fundamental problem in policy gradient-based methods in co...
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02/04/2019
The Natural Language of Actions
We introduce Act2Vec, a general framework for learning context-based act...
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02/16/2018
Train on Validation: Squeezing the Data Lemon
Model selection on validation data is an essential step in machine learn...
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11/22/2017
