Cover Image

Optimal-Point Variance Reduction For Bayesian Optimization With Regret Guarantee

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	Takeno, Shion
Format:	Preprint
Published:	2026
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

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

Improved Regret Analysis in Gaussian Process Bandits: Optimality for Noiseless Reward, RKHS norm, and Non-Stationary Variance
by: Iwazaki, Shogo, et al.
Published: (2025)

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

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

Regret Analysis of Posterior Sampling-Based Expected Improvement for Bayesian Optimization
by: Takeno, Shion, et al.
Published: (2025)

Regret Analysis for Randomized Gaussian Process Upper Confidence Bound
by: Takeno, Shion, et al.
Published: (2024)

Near-Optimal Algorithm for Non-Stationary Kernelized Bandits
by: Iwazaki, Shogo, et al.
Published: (2024)

Active Learning for Level Set Estimation Using Randomized Straddle Algorithms
by: Inatsu, Yu, et al.
Published: (2024)

Safe Distributionally Robust Feature Selection under Covariate Shift
by: Hanada, Hiroyuki, et al.
Published: (2026)

Bayesian Optimization from Human Feedback: Near-Optimal Regret Bounds
by: Kayal, Aya, et al.
Published: (2025)

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

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

Dose-finding design based on level set estimation in phase I cancer clinical trials
by: Seno, Keiichiro, et al.
Published: (2025)

Optimal Variance-Dependent Regret Bounds for Infinite-Horizon MDPs
by: Zamir, Guy, et al.
Published: (2026)

Targeted Variance Reduction: Robust Bayesian Optimization of Black-Box Simulators with Noise Parameters
by: Miller, John Joshua, et al.
Published: (2024)

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

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

Beyond Regrets: Geometric Metrics for Bayesian Optimization
by: Kim, Jungtaek
Published: (2024)

Regret Minimization via Saddle Point Optimization
by: Kirschner, Johannes, et al.
Published: (2024)

Minimax Optimal Variance-Aware Regret Bounds for Multinomial Logistic MDPs
by: Boudart, Pierre, et al.
Published: (2026)

Online Algorithms for Repeated Optimal Stopping: Balancing Baseline Guarantees and Regret
by: Harada, Tsubasa, et al.
Published: (2025)

Optimal Regret for Policy Optimization in Contextual Bandits
by: Levy, Orin, et al.
Published: (2026)

Bayesian Optimization with Expected Improvement: No Regret and the Choice of Incumbent
by: Wang, Jingyi, et al.
Published: (2025)

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

No-Regret Algorithms for Safe Bayesian Optimization with Monotonicity Constraints
by: Losalka, Arpan, et al.
Published: (2024)

Variance Reduction and Low Sample Complexity in Stochastic Optimization via Proximal Point Method
by: Liang, Jiaming
Published: (2024)

How Does Variance Shape the Regret in Contextual Bandits?
by: Jia, Zeyu, et al.
Published: (2024)

Batch Ensemble for Variance Dependent Regret in Stochastic Bandits
by: Cassel, Asaf, et al.
Published: (2024)

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

Variance Reduction Based Experience Replay for Policy Optimization
by: Zheng, Hua, et al.
Published: (2026)

Regret Guarantees for Linear Contextual Stochastic Shortest Path
by: Polikar, Dor, et al.
Published: (2025)

Data- and Variance-dependent Regret Bounds for Online Tabular MDPs
by: Li, Mingyi, et al.
Published: (2026)

Precise Asymptotics and Refined Regret of Variance-Aware UCB
by: Fan, Yingying, et al.
Published: (2024)

Variance-Dependent Regret Lower Bounds for Contextual Bandits
by: He, Jiafan, et al.
Published: (2025)

Regret-Based $(ε,δ)$-optimal Stopping Criteria for Bayesian Optimization
by: Wang, Haowei, et al.
Published: (2026)

Bayesian Optimization for Unknown Cost-Varying Variable Subsets with No-Regret Costs
by: Hoang, Vu Viet, et al.
Published: (2024)

Relaxing the Additivity Constraints in Decentralized No-Regret High-Dimensional Bayesian Optimization
by: Bardou, Anthony, et al.
Published: (2023)

Sharp Gap-Dependent Variance-Aware Regret Bounds for Tabular MDPs
by: Chen, Shulun, et al.
Published: (2025)

Clustering-based Meta Bayesian Optimization with Theoretical Guarantee
by: Nguyen, Khoa, et al.
Published: (2025)

Asymptotically Optimal Regret for Black-Box Predict-then-Optimize
by: Tan, Samuel, et al.
Published: (2024)