Cover Image

The Behavior and Convergence of Local Bayesian Optimization

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Wu, Kaiwen, Kim, Kyurae, Garnett, Roman, Gardner, Jacob R.
Format:	Preprint
Published:	2023
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

On the Convergence of Black-Box Variational Inference
by: Kim, Kyurae, et al.
Published: (2023)

Linear Convergence of Black-Box Variational Inference: Should We Stick the Landing?
by: Kim, Kyurae, et al.
Published: (2023)

Approximation-Aware Bayesian Optimization
by: Maus, Natalie, et al.
Published: (2024)

Nearly Dimension-Independent Convergence of Mean-Field Black-Box Variational Inference
by: Kim, Kyurae, et al.
Published: (2025)

Tuning Sequential Monte Carlo Samplers via Greedy Incremental Divergence Minimization
by: Kim, Kyurae, et al.
Published: (2025)

Provably Scalable Black-Box Variational Inference with Structured Variational Families
by: Ko, Joohwan, et al.
Published: (2024)

Demystifying SGD with Doubly Stochastic Gradients
by: Kim, Kyurae, et al.
Published: (2024)

A Fast, Robust Elliptical Slice Sampling Implementation for Linearly Truncated Multivariate Normal Distributions
by: Wu, Kaiwen, et al.
Published: (2024)

Understanding Stochastic Natural Gradient Variational Inference
by: Wu, Kaiwen, et al.
Published: (2024)

Knowledge Gradient for Preference Learning
by: Wu, Kaiwen, et al.
Published: (2026)

Stochastic Approximation with Biased MCMC for Expectation Maximization
by: Gruffaz, Samuel, et al.
Published: (2024)

Covering Multiple Objectives with a Small Set of Solutions Using Bayesian Optimization
by: Maus, Natalie, et al.
Published: (2025)

Stochastic Gradient Variational Inference with Price's Gradient Estimator from Bures-Wasserstein to Parameter Space
by: Kim, Kyurae, et al.
Published: (2026)

A Dynamic, Ordinal Gaussian Process Item Response Theoretic Model
by: Chen, Yehu, et al.
Published: (2025)

Idiographic Personality Gaussian Process for Psychological Assessment
by: Chen, Yehu, et al.
Published: (2024)

Amortized nonmyopic active search via deep imitation learning
by: Nguyen, Quan, et al.
Published: (2024)

Large-Scale Gaussian Processes via Alternating Projection
by: Wu, Kaiwen, et al.
Published: (2023)

We Still Don't Understand High-Dimensional Bayesian Optimization
by: Doumont, Colin, et al.
Published: (2025)

A Theoretical Comparison of No-U-Turn Sampler Variants: Necessary and Sufficient Convergence Conditions and Mixing Time Analysis under Gaussian Targets
by: Gruffaz, Samuel, et al.
Published: (2026)

Adversarial Query Synthesis via Bayesian Optimization
by: Tao, Jeffrey, et al.
Published: (2026)

Computation-Aware Gaussian Processes: Model Selection And Linear-Time Inference
by: Wenger, Jonathan, et al.
Published: (2024)

Local Constrained Bayesian Optimization
by: Jingzhe, Jing, et al.
Published: (2026)

Local Preferential Bayesian Optimization
by: Menn, Johanna, et al.
Published: (2026)

Purely Agent-Driven Black-Box Optimization for Biological Design
by: Maus, Natalie, et al.
Published: (2026)

Trading Convergence Rate with Computational Budget in High Dimensional Bayesian Optimization
by: Tran-The, Hung, et al.
Published: (2019)

Large Scale Multi-Task Bayesian Optimization with Large Language Models
by: Zeng, Yimeng, et al.
Published: (2025)

Robust Bayesian Optimization via Localized Online Conformal Prediction
by: Kim, Dongwon, et al.
Published: (2024)

Convergence of Distributed Adaptive Optimization with Local Updates
by: Cheng, Ziheng, et al.
Published: (2024)

Analysis of kinetic Langevin Monte Carlo under the stochastic exponential Euler discretization from underdamped all the way to overdamped
by: Kim, Kyurae, et al.
Published: (2025)

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

Local Linear Convergence of Infeasible Optimization with Orthogonal Constraints
by: Sun, Youbang, et al.
Published: (2024)

Analyzing and Enhancing the Backward-Pass Convergence of Unrolled Optimization
by: Kotary, James, et al.
Published: (2023)

Exponential Convergence of CAVI for Bayesian PCA
by: Datta, Arghya, et al.
Published: (2025)

On the Convergence of Locally Adaptive and Scalable Diffusion-Based Sampling Methods for Deep Bayesian Neural Network Posteriors
by: Rensmeyer, Tim, et al.
Published: (2024)

Differentially Private Hyperparameter Tuning using Local Bayesian Optimization
by: Sopa, Getoar, et al.
Published: (2025)

Aligning Diffusion Behaviors with Q-functions for Efficient Continuous Control
by: Chen, Huayu, et al.
Published: (2024)

Accelerating Convergence in Bayesian Few-Shot Classification
by: Ke, Tianjun, et al.
Published: (2024)

Density Ratio Estimation-based Bayesian Optimization with Semi-Supervised Learning
by: Kim, Jungtaek
Published: (2023)

Iterate to Accelerate: A Unified Framework for Iterative Reasoning and Feedback Convergence
by: Fein-Ashley, Jacob
Published: (2025)

Convergence Behavior of an Adversarial Weak Supervision Method
by: An, Steven, et al.
Published: (2024)