Copertina

Bayesian Off-Policy Evaluation and Learning for Large Action Spaces

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Aouali, Imad, Brunel, Victor-Emmanuel, Rohde, David, Korba, Anna
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Unified PAC-Bayesian Study of Pessimism for Offline Policy Learning with Regularized Importance Sampling
di: Aouali, Imad, et al.
Pubblicazione: (2024)

Off-Policy Learning in Large Action Spaces: Optimization Matters More Than Estimation
di: Aouali, Imad, et al.
Pubblicazione: (2025)

Diffusion Models Meet Contextual Bandits
di: Aouali, Imad
Pubblicazione: (2024)

Logarithmic Smoothing for Pessimistic Off-Policy Evaluation, Selection and Learning
di: Sakhi, Otmane, et al.
Pubblicazione: (2024)

Learning Action Embeddings for Off-Policy Evaluation
di: Cief, Matej, et al.
Pubblicazione: (2023)

RecoAtlas: From Semantic Plausibility to Set-Level Utility in LLM Recommendation Agents
di: Aouali, Imad, et al.
Pubblicazione: (2026)

Off-OAB: Off-Policy Policy Gradient Method with Optimal Action-Dependent Baseline
di: Meng, Wenjia, et al.
Pubblicazione: (2024)

Kernel Metric Learning for In-Sample Off-Policy Evaluation of Deterministic RL Policies
di: Lee, Haanvid, et al.
Pubblicazione: (2024)

Effective Off-Policy Evaluation and Learning in Contextual Combinatorial Bandits
di: Shimizu, Tatsuhiro, et al.
Pubblicazione: (2024)

Off-Policy Evaluation and Learning for the Future under Non-Stationarity
di: Shimizu, Tatsuhiro, et al.
Pubblicazione: (2025)

Concept-driven Off Policy Evaluation
di: Majumdar, Ritam, et al.
Pubblicazione: (2024)

Clustering Context in Off-Policy Evaluation
di: Guzman-Olivares, Daniel, et al.
Pubblicazione: (2025)

Action-Adaptive Continual Learning: Enabling Policy Generalization under Dynamic Action Spaces
di: Pan, Chaofan, et al.
Pubblicazione: (2025)

Off-Policy Evaluation and Learning for Survival Outcomes under Censoring
di: Kubota, Kohsuke, et al.
Pubblicazione: (2026)

Zero-Shot Off-Policy Learning
di: Asadulaev, Arip, et al.
Pubblicazione: (2026)

Evaluating the Relevance of Uncertainty Estimators for LLM Hallucination
di: Agnimo, Yedidia, et al.
Pubblicazione: (2026)

SCOPE-RL: A Python Library for Offline Reinforcement Learning and Off-Policy Evaluation
di: Kiyohara, Haruka, et al.
Pubblicazione: (2023)

Discretizing Continuous Action Space with Unimodal Probability Distributions for On-Policy Reinforcement Learning
di: Zhu, Yuanyang, et al.
Pubblicazione: (2024)

A Unifying View of Coverage in Linear Off-Policy Evaluation
di: Amortila, Philip, et al.
Pubblicazione: (2026)

Towards Off-Policy Reinforcement Learning for Ranking Policies with Human Feedback
di: Xiao, Teng, et al.
Pubblicazione: (2024)

Policy Learning for Off-Dynamics RL with Deficient Support
di: Van, Linh Le Pham, et al.
Pubblicazione: (2024)

An Advantage-based Optimization Method for Reinforcement Learning in Large Action Space
di: Lin, Hai, et al.
Pubblicazione: (2024)

Balancing Immediate Revenue and Future Off-Policy Evaluation in Coupon Allocation
di: Nishimura, Naoki, et al.
Pubblicazione: (2024)

Efficient and Sharp Off-Policy Evaluation in Robust Markov Decision Processes
di: Bennett, Andrew, et al.
Pubblicazione: (2024)

SOPE: Stabilizing Off-Policy Evaluation for Online RL with Prior Data
di: Romeo, Carlo, et al.
Pubblicazione: (2026)

Statistical Tractability of Off-policy Evaluation of History-dependent Policies in POMDPs
di: Zhang, Yuheng, et al.
Pubblicazione: (2025)

Towards Assessing and Benchmarking Risk-Return Tradeoff of Off-Policy Evaluation
di: Kiyohara, Haruka, et al.
Pubblicazione: (2023)

Demystifying the Paradox of Importance Sampling with an Estimated History-Dependent Behavior Policy in Off-Policy Evaluation
di: Zhou, Hongyi, et al.
Pubblicazione: (2025)

Soft Policy Optimization: Online Off-Policy RL for Sequence Models
di: Cohen, Taco, et al.
Pubblicazione: (2025)

SAINT: Attention-Based Policies for Discrete Combinatorial Action Spaces
di: Landers, Matthew, et al.
Pubblicazione: (2025)

Data Poisoning Attacks on Off-Policy Policy Evaluation Methods
di: Lobo, Elita, et al.
Pubblicazione: (2024)

Low-Rank Adaptation for Critic Learning in Off-Policy Reinforcement Learning
di: Zhuang, Yuan, et al.
Pubblicazione: (2026)

Large Language Model Post-Training: A Unified View of Off-Policy and On-Policy Learning
di: Zhao, Shiwan, et al.
Pubblicazione: (2026)

Automated Off-Policy Estimator Selection via Supervised Learning
di: Felicioni, Nicolò, et al.
Pubblicazione: (2024)

Scaling Off-Policy Reinforcement Learning with Batch and Weight Normalization
di: Palenicek, Daniel, et al.
Pubblicazione: (2025)

Prior-Dependent Allocations for Bayesian Fixed-Budget Best-Arm Identification in Structured Bandits
di: Nguyen, Nicolas, et al.
Pubblicazione: (2024)

Generalized Discrete Diffusion from Snapshots
di: Zekri, Oussama, et al.
Pubblicazione: (2026)

Breaking the Grid: Distance-Guided Reinforcement Learning in Large Discrete Action Spaces
di: Hoppe, Heiko, et al.
Pubblicazione: (2026)

Abstract Reward Processes: Leveraging State Abstraction for Consistent Off-Policy Evaluation
di: Chaudhari, Shreyas, et al.
Pubblicazione: (2024)

Q-MMR: Off-Policy Evaluation via Recursive Reweighting and Moment Matching
di: Li, Xiang, et al.
Pubblicazione: (2026)