Efficient and Sharp Off-Policy Evaluation in Robust Markov Decision Processes
Fuente:
arXiv
Saved in:
| Main Authors: | Bennett, Andrew, Kallus, Nathan, Oprescu, Miruna, Sun, Wen, Wang, Kaiwen |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Low-Rank MDPs with Continuous Action Spaces
by: Bennett, Andrew, et al.
Published: (2023)
by: Bennett, Andrew, et al.
Published: (2023)
Robust and Agnostic Learning of Conditional Distributional Treatment Effects
by: Kallus, Nathan, et al.
Published: (2022)
by: Kallus, Nathan, et al.
Published: (2022)
Estimating Heterogeneous Treatment Effects by Combining Weak Instruments and Observational Data
by: Oprescu, Miruna, et al.
Published: (2024)
by: Oprescu, Miruna, et al.
Published: (2024)
Efficient Adaptive Experimentation with Noncompliance
by: Oprescu, Miruna, et al.
Published: (2025)
by: Oprescu, Miruna, et al.
Published: (2025)
Conformal Off-Policy Evaluation in Markov Decision Processes
by: Foffano, Daniele, et al.
Published: (2023)
by: Foffano, Daniele, et al.
Published: (2023)
Policy Gradient for Robust Markov Decision Processes
by: Wang, Qiuhao, et al.
Published: (2024)
by: Wang, Qiuhao, et al.
Published: (2024)
The Context Gathering Decision Process: A POMDP Framework for Agentic Search
by: Kausik, Chinmaya, et al.
Published: (2026)
by: Kausik, Chinmaya, et al.
Published: (2026)
Causal Inference on Networks under Misspecified Exposure Mappings: A Partial Identification Framework
by: Schröder, Maresa, et al.
Published: (2026)
by: Schröder, Maresa, et al.
Published: (2026)
SCENT: Robust Spatiotemporal Learning for Continuous Scientific Data via Scalable Conditioned Neural Fields
by: Park, David Keetae, et al.
Published: (2025)
by: Park, David Keetae, et al.
Published: (2025)
Value-Guided Search for Efficient Chain-of-Thought Reasoning
by: Wang, Kaiwen, et al.
Published: (2025)
by: Wang, Kaiwen, et al.
Published: (2025)
Solving Robust Markov Decision Processes: Generic, Reliable, Efficient
by: Meggendorfer, Tobias, et al.
Published: (2024)
by: Meggendorfer, Tobias, et al.
Published: (2024)
Semiparametric Preference Optimization: Your Language Model is Secretly a Single-Index Model
by: Kallus, Nathan
Published: (2025)
by: Kallus, Nathan
Published: (2025)
Optimal Decision Tree Policies for Markov Decision Processes
by: Vos, Daniël, et al.
Published: (2023)
by: Vos, Daniël, et al.
Published: (2023)
Policy Regularized Distributionally Robust Markov Decision Processes with Linear Function Approximation
by: Gu, Jingwen, et al.
Published: (2025)
by: Gu, Jingwen, et al.
Published: (2025)
GST-UNet: A Neural Framework for Spatiotemporal Causal Inference with Time-Varying Confounding
by: Oprescu, Miruna, et al.
Published: (2025)
by: Oprescu, Miruna, et al.
Published: (2025)
Robust Lagrangian and Adversarial Policy Gradient for Robust Constrained Markov Decision Processes
by: Bossens, David M.
Published: (2023)
by: Bossens, David M.
Published: (2023)
SPOT: Scalable Policy Optimization with Trees for Markov Decision Processes
by: Xiong, Xuyuan, et al.
Published: (2025)
by: Xiong, Xuyuan, et al.
Published: (2025)
Linear Mixture Distributionally Robust Markov Decision Processes
by: Liu, Zhishuai, et al.
Published: (2025)
by: Liu, Zhishuai, et al.
Published: (2025)
Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes
by: Kumar, Navdeep, et al.
Published: (2025)
by: Kumar, Navdeep, et al.
Published: (2025)
Policy Gradient Algorithms with Monte Carlo Tree Learning for Non-Markov Decision Processes
by: Morimura, Tetsuro, et al.
Published: (2022)
by: Morimura, Tetsuro, et al.
Published: (2022)
Markov Decision Processes under External Temporal Processes
by: Ayyagari, Ranga Shaarad, et al.
Published: (2023)
by: Ayyagari, Ranga Shaarad, et al.
Published: (2023)
Provably Efficient Reward Transfer in Reinforcement Learning with Discrete Markov Decision Processes
by: Vora, Kevin, et al.
Published: (2025)
by: Vora, Kevin, et al.
Published: (2025)
$Q\sharp$: Provably Optimal Distributional RL for LLM Post-Training
by: Zhou, Jin Peng, et al.
Published: (2025)
by: Zhou, Jin Peng, et al.
Published: (2025)
Regret Analysis of Policy Gradient Algorithm for Infinite Horizon Average Reward Markov Decision Processes
by: Bai, Qinbo, et al.
Published: (2023)
by: Bai, Qinbo, et al.
Published: (2023)
Abstract Reward Processes: Leveraging State Abstraction for Consistent Off-Policy Evaluation
by: Chaudhari, Shreyas, et al.
Published: (2024)
by: Chaudhari, Shreyas, et al.
Published: (2024)
The Central Role of the Loss Function in Reinforcement Learning
by: Wang, Kaiwen, et al.
Published: (2024)
by: Wang, Kaiwen, et al.
Published: (2024)
SOPE: Stabilizing Off-Policy Evaluation for Online RL with Prior Data
by: Romeo, Carlo, et al.
Published: (2026)
by: Romeo, Carlo, et al.
Published: (2026)
Concept-driven Off Policy Evaluation
by: Majumdar, Ritam, et al.
Published: (2024)
by: Majumdar, Ritam, et al.
Published: (2024)
Clustering Context in Off-Policy Evaluation
by: Guzman-Olivares, Daniel, et al.
Published: (2025)
by: Guzman-Olivares, Daniel, et al.
Published: (2025)
An Offline Risk-aware Policy Selection Method for Bayesian Markov Decision Processes
by: Angelotti, Giorgio, et al.
Published: (2021)
by: Angelotti, Giorgio, et al.
Published: (2021)
OCMDP: Observation-Constrained Markov Decision Process
by: Wang, Taiyi, et al.
Published: (2024)
by: Wang, Taiyi, et al.
Published: (2024)
Learning Action Embeddings for Off-Policy Evaluation
by: Cief, Matej, et al.
Published: (2023)
by: Cief, Matej, et al.
Published: (2023)
On the Convergence of Modified Policy Iteration in Risk Sensitive Exponential Cost Markov Decision Processes
by: Murthy, Yashaswini, et al.
Published: (2023)
by: Murthy, Yashaswini, et al.
Published: (2023)
Breaking the Curse of Repulsion: Optimistic Distributionally Robust Policy Optimization for Off-Policy Generative Recommendation
by: Jiang, Jie, et al.
Published: (2026)
by: Jiang, Jie, et al.
Published: (2026)
Act as You Learn: Adaptive Decision-Making in Non-Stationary Markov Decision Processes
by: Luo, Baiting, et al.
Published: (2024)
by: Luo, Baiting, et al.
Published: (2024)
Hierarchical Average-Reward Linearly-solvable Markov Decision Processes
by: Infante, Guillermo, et al.
Published: (2024)
by: Infante, Guillermo, et al.
Published: (2024)
Adjusting Regression Models for Conditional Uncertainty Calibration
by: Gao, Ruijiang, et al.
Published: (2024)
by: Gao, Ruijiang, et al.
Published: (2024)
Off-Policy Actor-Critic for Adversarial Observation Robustness: Virtual Alternative Training via Symmetric Policy Evaluation
by: Nakanishi, Kosuke, et al.
Published: (2025)
by: Nakanishi, Kosuke, et al.
Published: (2025)
Optimistic Regret Bounds for Online Learning in Adversarial Markov Decision Processes
by: Moon, Sang Bin, et al.
Published: (2024)
by: Moon, Sang Bin, et al.
Published: (2024)
Diffusion-Augmented Markov Decision Processes for Maximum Entropy Reinforcement Learning
by: Sanokowski, Sebastian, et al.
Published: (2025)
by: Sanokowski, Sebastian, et al.
Published: (2025)
Similar Items
-
Low-Rank MDPs with Continuous Action Spaces
by: Bennett, Andrew, et al.
Published: (2023) -
Robust and Agnostic Learning of Conditional Distributional Treatment Effects
by: Kallus, Nathan, et al.
Published: (2022) -
Estimating Heterogeneous Treatment Effects by Combining Weak Instruments and Observational Data
by: Oprescu, Miruna, et al.
Published: (2024) -
Efficient Adaptive Experimentation with Noncompliance
by: Oprescu, Miruna, et al.
Published: (2025) -
Conformal Off-Policy Evaluation in Markov Decision Processes
by: Foffano, Daniele, et al.
Published: (2023)