Cover Image

Bayesian Optimization from Human Feedback: Near-Optimal Regret Bounds

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Kayal, Aya, Vakili, Sattar, Toni, Laura, Shiu, Da-shan, Bernacchia, Alberto
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Near-Optimal Sample Complexity in Reward-Free Kernel-Based Reinforcement Learning
by: Kayal, Aya, et al.
Published: (2025)

Reinforcement Learning Using known Invariances
by: Cioba, Alexandru, et al.
Published: (2025)

A Finite Time Analysis of Thompson Sampling for Bayesian Optimization with Preferential Feedback
by: Lazzaro, Joseph, et al.
Published: (2026)

Open Problem: Order Optimal Regret Bounds for Kernel-Based Reinforcement Learning
by: Vakili, Sattar
Published: (2024)

Kernelized Reinforcement Learning with Order Optimal Regret Bounds
by: Vakili, Sattar, et al.
Published: (2023)

Random Exploration in Bayesian Optimization: Order-Optimal Regret and Computational Efficiency
by: Salgia, Sudeep, et al.
Published: (2023)

Kernel-Based Function Approximation for Average Reward Reinforcement Learning: An Optimist No-Regret Algorithm
by: Vakili, Sattar, et al.
Published: (2024)

Exact, Tractable Gauss-Newton Optimization in Deep Reversible Architectures Reveal Poor Generalization
by: Buffelli, Davide, et al.
Published: (2024)

The impact of intrinsic rewards on exploration in Reinforcement Learning
by: Kayal, Aya, et al.
Published: (2025)

Learning Kernel-Based MDPs from Episodic Preferential Feedback
by: Pavlovic, Nikola, et al.
Published: (2026)

No-Regret Thompson Sampling for Finite-Horizon Markov Decision Processes with Gaussian Processes
by: Bayrooti, Jasmine, et al.
Published: (2025)

Towards a Foundation Model for Communication Systems
by: Buffelli, Davide, et al.
Published: (2025)

Near-Optimal Regret in Linear MDPs with Aggregate Bandit Feedback
by: Cassel, Asaf, et al.
Published: (2024)

Stopping Bayesian Optimization with Probabilistic Regret Bounds
by: Wilson, James T.
Published: (2024)

On Regret Bounds of Thompson Sampling for Bayesian Optimization
by: Takeno, Shion, et al.
Published: (2026)

Information Capacity Regret Bounds for Bandits with Mediator Feedback
by: Eldowa, Khaled, et al.
Published: (2024)

On Improved Regret Bounds In Bayesian Optimization with Gaussian Noise
by: Wang, Jingyi, et al.
Published: (2024)

Posterior Sampling-Based Bayesian Optimization with Tighter Bayesian Regret Bounds
by: Takeno, Shion, et al.
Published: (2023)

Bayesian Optimisation with Unknown Hyperparameters: Regret Bounds Logarithmically Closer to Optimal
by: Ziomek, Juliusz, et al.
Published: (2024)

Improved Regret Bounds for Gaussian Process Upper Confidence Bound in Bayesian Optimization
by: Iwazaki, Shogo
Published: (2025)

Randomized Kriging Believer for Parallel Bayesian Optimization with Regret Bounds
by: Sugiura, Shuhei, et al.
Published: (2026)

Data-Driven Upper Confidence Bounds with Near-Optimal Regret for Heavy-Tailed Bandits
by: Tamás, Ambrus, et al.
Published: (2024)

Optimal-Point Variance Reduction For Bayesian Optimization With Regret Guarantee
by: Takeno, Shion
Published: (2026)

Tight Regret Bounds for Bayesian Optimization in One Dimension
by: Scarlett, Jonathan
Published: (2018)

Near-optimal Regret Using Policy Optimization in Online MDPs with Aggregate Bandit Feedback
by: Lancewicki, Tal, et al.
Published: (2025)

Identification and Adaptive Control of Markov Jump Systems: Sample Complexity and Regret Bounds
by: Sattar, Yahya, et al.
Published: (2021)

Near-Optimal Regret in Adversarial Kernel Bandits
by: Zhang, Yu-Jie, et al.
Published: (2026)

Direct Regret Optimization in Bayesian Optimization
by: Zhang, Fengxue, et al.
Published: (2025)

Optimal High-Probability Regret for Online Convex Optimization with Two-Point Bandit Feedback
by: Ye, Haishan
Published: (2026)

Near-Optimal Regret for Policy Optimization in Contextual MDPs with General Offline Function Approximation
by: Levy, Orin, et al.
Published: (2026)

Near-optimal Per-Action Regret Bounds for Sleeping Bandits
by: Nguyen, Quan, et al.
Published: (2024)

Nearly Minimax Optimal Regret for Multinomial Logistic Bandit
by: Lee, Joongkyu, et al.
Published: (2024)

Gaussian Process Upper Confidence Bound Achieves Nearly-Optimal Regret in Noise-Free Gaussian Process Bandits
by: Iwazaki, Shogo
Published: (2025)

Rethinking the shape convention of an MLP
by: Chen, Meng-Hsi, et al.
Published: (2025)

Order Optimal Regret Bounds for Sharpe Ratio Optimization under Thompson Sampling
by: Shah, Mohammad Taha, et al.
Published: (2025)

Near-Optimal Dynamic Regret for Adversarial Linear Mixture MDPs
by: Li, Long-Fei, et al.
Published: (2024)

Optimal Bayesian Affine Estimator and Active Learning for the Wiener Model
by: Vakili, Sasan, et al.
Published: (2025)

Wasserstein Distributionally Robust Regret Optimization for Reinforcement Learning from Human Feedback
by: Wang, Yikai, et al.
Published: (2026)

Improved Regret for Bandit Convex Optimization with Delayed Feedback
by: Wan, Yuanyu, et al.
Published: (2024)

Optimal Strong Regret and Violation in Constrained MDPs via Policy Optimization
by: Stradi, Francesco Emanuele, et al.
Published: (2024)