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07/25/2023
Source Condition Double Robust Inference on Functionals of Inverse Problems
We consider estimation of parameters defined as linear functionals of so...
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06/26/2023
Off-Policy Evaluation of Ranking Policies under Diverse User Behavior
Ranking interfaces are everywhere in online platforms. There is thus an ...
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05/29/2023
How to Query Human Feedback Efficiently in RL?
Reinforcement Learning with Human Feedback (RLHF) is a paradigm in which...
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05/24/2023
Provable Offline Reinforcement Learning with Human Feedback
In this paper, we investigate the problem of offline reinforcement learn...
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02/19/2023
Distributional Offline Policy Evaluation with Predictive Error Guarantees
We study the problem of estimating the distribution of the return of a p...
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02/10/2023
Minimax Instrumental Variable Regression and L_2 Convergence Guarantees without Identification or Closedness
In this paper, we study nonparametric estimation of instrumental variabl...
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02/05/2023
Refined Value-Based Offline RL under Realizability and Partial Coverage
In offline reinforcement learning (RL) we have no opportunity to explore...
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12/13/2022
A Review of Off-Policy Evaluation in Reinforcement Learning
Reinforcement learning (RL) is one of the most vibrant research frontier...
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07/26/2022
Future-Dependent Value-Based Off-Policy Evaluation in POMDPs
We study off-policy evaluation (OPE) for partially observable MDPs (POMD...
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07/12/2022
PAC Reinforcement Learning for Predictive State Representations
In this paper we study online Reinforcement Learning (RL) in partially o...
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06/24/2022
Computationally Efficient PAC RL in POMDPs with Latent Determinism and Conditional Embeddings
We study reinforcement learning with function approximation for large-sc...
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06/24/2022
Provably Efficient Reinforcement Learning in Partially Observable Dynamical Systems
We study Reinforcement Learning for partially observable dynamical syste...
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01/31/2022
Efficient Reinforcement Learning in Block MDPs: A Model-free Representation Learning Approach
We present BRIEE (Block-structured Representation learning with Interlea...
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01/12/2022
Best Arm Identification with a Fixed Budget under a Small Gap
We consider the fixed-budget best arm identification problem in the mult...
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11/12/2021
A Minimax Learning Approach to Off-Policy Evaluation in Partially Observable Markov Decision Processes
We consider off-policy evaluation (OPE) in Partially Observable Markov D...
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10/09/2021
Representation Learning for Online and Offline RL in Low-rank MDPs
This work studies the question of Representation Learning in RL: how can...
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07/13/2021
Pessimistic Model-based Offline RL: PAC Bounds and Posterior Sampling under Partial Coverage
We study model-based offline Reinforcement Learning with general functio...
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06/06/2021
Mitigating Covariate Shift in Imitation Learning via Offline Data Without Great Coverage
This paper studies offline Imitation Learning (IL) where an agent learns...
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03/25/2021
Causal Inference Under Unmeasured Confounding With Negative Controls: A Minimax Learning Approach
We study the estimation of causal parameters when not all confounders ar...
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02/05/2021
Finite Sample Analysis of Minimax Offline Reinforcement Learning: Completeness, Fast Rates and First-Order Efficiency
We offer a theoretical characterization of off-policy evaluation (OPE) i...
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01/31/2021
Fast Rates for the Regret of Offline Reinforcement Learning
We study the regret of reinforcement learning from offline data generate...
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10/21/2020
Optimal Off-Policy Evaluation from Multiple Logging Policies
We study off-policy evaluation (OPE) from multiple logging policies, eac...
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06/06/2020
Doubly Robust Off-Policy Value and Gradient Estimation for Deterministic Policies
Offline reinforcement learning, wherein one uses off-policy data logged ...
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06/06/2020
Efficient Evaluation of Natural Stochastic Policies in Offline Reinforcement Learning
We study the efficient off-policy evaluation of natural stochastic polic...
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02/26/2020
Off-Policy Evaluation and Learning for External Validity under a Covariate Shift
We consider the evaluation and training of a new policy for the evaluati...
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02/10/2020
Statistically Efficient Off-Policy Policy Gradients
Policy gradient methods in reinforcement learning update policy paramete...
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12/30/2019
Localized Debiased Machine Learning: Efficient Estimation of Quantile Treatment Effects, Conditional Value at Risk, and Beyond
We consider the efficient estimation of a low-dimensional parameter in t...
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10/28/2019
Minimax Weight and Q-Function Learning for Off-Policy Evaluation
We provide theoretical investigations into off-policy evaluation in rein...
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09/12/2019
Efficiently Breaking the Curse of Horizon: Double Reinforcement Learning in Infinite-Horizon Processes
Off-policy evaluation (OPE) in reinforcement learning is notoriously dif...
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08/22/2019
Double Reinforcement Learning for Efficient Off-Policy Evaluation in Markov Decision Processes
Off-policy evaluation (OPE) in reinforcement learning allows one to eval...
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06/09/2019
Intrinsically Efficient, Stable, and Bounded Off-Policy Evaluation for Reinforcement Learning
Off-policy evaluation (OPE) in both contextual bandits and reinforcement...
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05/15/2019
Information criteria for non-normalized models
Many statistical models are given in the form of non-normalized densitie...
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03/08/2019
Imputation estimators for unnormalized models with missing data
We propose estimation methods for unnormalized models with missing data....
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01/23/2019
Unified estimation framework for unnormalized models with statistical efficiency
Parameter estimation of unnormalized models is a challenging problem bec...
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01/23/2019
Unified efficient estimation framework for unnormalized models
Parameter estimation of unnormalized models is a challenging problem bec...
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10/30/2018
Semiparametric response model with nonignorable nonresponse
How to deal with nonignorable response is often a challenging problem en...
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08/24/2018
Analysis of Noise Contrastive Estimation from the Perspective of Asymptotic Variance
There are many models, often called unnormalized models, whose normalizi...
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10/10/2016