Cover Image

Batch Acquisition Function Evaluations and Decouple Optimizer Updates for Faster Bayesian Optimization

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Irie, Kaichi, Watanabe, Shuhei, Onishi, Masaki
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Speeding Up Multi-Objective Hyperparameter Optimization by Task Similarity-Based Meta-Learning for the Tree-Structured Parzen Estimator
by: Watanabe, Shuhei, et al.
Published: (2022)

Approximation of Box Decomposition Algorithm for Fast Hypervolume-Based Multi-Objective Optimization
by: Watanabe, Shuhei
Published: (2025)

c-TPE: Tree-structured Parzen Estimator with Inequality Constraints for Expensive Hyperparameter Optimization
by: Watanabe, Shuhei, et al.
Published: (2022)

OptunaHub: A Platform for Black-Box Optimization
by: Ozaki, Yoshihiko, et al.
Published: (2025)

Tree-Structured Parzen Estimator Can Solve Black-Box Combinatorial Optimization More Efficiently
by: Abe, Kenshin, et al.
Published: (2025)

Pareto Front-Diverse Batch Multi-Objective Bayesian Optimization
by: Ahmadianshalchi, Alaleh, et al.
Published: (2024)

Multi-Agent LLMs for Adaptive Acquisition in Bayesian Optimization
by: Carbonati, Andrea, et al.
Published: (2026)

Fast Benchmarking of Asynchronous Multi-Fidelity Optimization on Zero-Cost Benchmarks
by: Watanabe, Shuhei, et al.
Published: (2024)

Derivation of Output Correlation Inferences for Multi-Output (aka Multi-Task) Gaussian Process
by: Watanabe, Shuhei
Published: (2025)

Derivation of Closed Form of Expected Improvement for Gaussian Process Trained on Log-Transformed Objective
by: Watanabe, Shuhei
Published: (2024)

Tree-Structured Parzen Estimator: Understanding Its Algorithm Components and Their Roles for Better Empirical Performance
by: Watanabe, Shuhei
Published: (2023)

Adaptive Acquisition Selection for Bayesian Optimization with Large Language Models
by: Ngo, Giang, et al.
Published: (2026)

A Simple and Efficient Approach to Batch Bayesian Optimization
by: Zhan, Dawei, et al.
Published: (2024)

BOTS: Batch Bayesian Optimization of Extended Thompson Sampling for Severely Episode-Limited RL Settings
by: Karine, Karine, et al.
Published: (2024)

Batch Bayesian Active Learning with Partial Batch Label Sampling
by: Hu, Kangping, et al.
Published: (2025)

Large-Batch, Iteration-Efficient Neural Bayesian Design Optimization
by: Ansari, Navid, et al.
Published: (2023)

DeMo: Decoupled Momentum Optimization
by: Peng, Bowen, et al.
Published: (2024)

Adaptive Batch-Wise Sample Scheduling for Direct Preference Optimization
by: Huang, Zixuan, et al.
Published: (2025)

FedLion: Faster Adaptive Federated Optimization with Fewer Communication
by: Tang, Zhiwei, et al.
Published: (2024)

Conditional PED-ANOVA: Hyperparameter Importance in Hierarchical & Dynamic Search Spaces
by: Baba, Kaito, et al.
Published: (2026)

Tula: Optimizing Time, Cost, and Generalization in Distributed Large-Batch Training
by: Tyagi, Sahil, et al.
Published: (2026)

Bayesian Optimization for Function-Valued Responses under Min-Max Criteria
by: Ahadi, Pouya, et al.
Published: (2025)

Explainable Bayesian Optimization
by: Chakraborty, Tanmay, et al.
Published: (2024)

On Surprising Effectiveness of Masking Updates in Adaptive Optimizers
by: Joo, Taejong, et al.
Published: (2026)

Pretrain Value, Not Reward: Decoupled Value Policy Optimization
by: Huang, Chenghua, et al.
Published: (2025)

Trust the Batch, On- or Off-Policy: Adaptive Policy Optimization for RL Post-Training
by: Fakoor, Rasool, et al.
Published: (2026)

Optimizing Data Curation through Spectral Analysis and Joint Batch Selection (SALN)
by: Sharifi, Mohammadreza
Published: (2024)

Poisson Process for Bayesian Optimization
by: Wang, Xiaoxing, et al.
Published: (2024)

Towards Flash Thinking via Decoupled Advantage Policy Optimization
by: Tan, Zezhong, et al.
Published: (2025)

DRPO: Efficient Reasoning via Decoupled Reward Policy Optimization
by: Li, Gang, et al.
Published: (2025)

Open-Ended Task Discovery via Bayesian Optimization
by: Adachi, Masaki, et al.
Published: (2026)

Training Greedy Policy for Proposal Batch Selection in Expensive Multi-Objective Combinatorial Optimization
by: Lee, Deokjae, et al.
Published: (2024)

Optimizing Predictive AI in Physical Design Flows with Mini Pixel Batch Gradient Descent
by: Yang, Haoyu, et al.
Published: (2024)

Towards Faster Decentralized Stochastic Optimization with Communication Compression
by: Islamov, Rustem, et al.
Published: (2024)

Inversion-based Latent Bayesian Optimization
by: Chu, Jaewon, et al.
Published: (2024)

Information-Theoretic Safe Bayesian Optimization
by: Bottero, Alessandro G., et al.
Published: (2024)

ORTHOBO: Orthogonal Bayesian Hyperparameter Optimization
by: Schröder, Maresa, et al.
Published: (2026)

XShare: Collaborative in-Batch Expert Sharing for Faster MoE Inference
by: Vankov, Daniil, et al.
Published: (2026)

MT-DAO: Multi-Timescale Distributed Adaptive Optimizers with Local Updates
by: Iacob, Alex, et al.
Published: (2025)

High-Dimensional Search, Low-Dimensional Solution: Decoupling Optimization from Representation
by: Kalyoncuoglu, Yusuf, et al.
Published: (2025)