Cover Image

An Empirical Study on Ensemble-Based Transfer Learning Bayesian Optimisation with Mixed Variable Types

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Trinkle, Natasha, Ha, Huong, Chan, Jeffrey
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

MOCA-HESP: Meta High-dimensional Bayesian Optimization for Combinatorial and Mixed Spaces via Hyper-ellipsoid Partitioning
by: Ngo, Lam, et al.
Published: (2025)

MOBO-OSD: Batch Multi-Objective Bayesian Optimization via Orthogonal Search Directions
by: Ngo, Lam, et al.
Published: (2025)

BOIDS: High-dimensional Bayesian Optimization via Incumbent-guided Direction Lines and Subspace Embeddings
by: Ngo, Lam, et al.
Published: (2024)

High-dimensional Bayesian Optimization via Covariance Matrix Adaptation Strategy
by: Ngo, Lam, et al.
Published: (2024)

Sub-linear Regret Bounds for Bayesian Optimisation in Unknown Search Spaces
by: Tran-The, Hung, et al.
Published: (2020)

Ensemble Distributionally Robust Bayesian Optimisation
by: Ramazyan, Tigran, et al.
Published: (2026)

Explainable Machine Learning for Oxygen Diffusion in Perovskites and Pyrochlores
by: Lu, Grace M., et al.
Published: (2025)

Data-driven Prior Learning for Bayesian Optimisation
by: Hellan, Sigrid Passano, et al.
Published: (2023)

Bayesian Ensembling: Insights from Online Optimization and Empirical Bayes
by: Waxman, Daniel, et al.
Published: (2025)

An Empirical Study of $μ$P Learning Rate Transfer
by: Lingle, Lucas
Published: (2024)

Contextual Causal Bayesian Optimisation
by: Arsenyan, Vahan, et al.
Published: (2023)

Cross-model Fairness: Empirical Study of Fairness and Ethics Under Model Multiplicity
by: Sokol, Kacper, et al.
Published: (2022)

Developing An Attention-Based Ensemble Learning Framework for Financial Portfolio Optimisation
by: Li, Zhenglong, et al.
Published: (2024)

Provably Efficient Bayesian Optimization with Unknown Gaussian Process Hyperparameter Estimation
by: Ha, Huong, et al.
Published: (2023)

An Empirical Study of Scaling Laws for Transfer
by: Barnett, Matthew
Published: (2024)

Graph Agnostic Causal Bayesian Optimisation
by: Mukherjee, Sumantrak, et al.
Published: (2024)

Robust Bayesian Optimisation with Unbounded Corruptions
by: Ezzerg, Abdelhamid, et al.
Published: (2025)

Empirical Bayesian Multi-Bandit Learning
by: Jiang, Xia, et al.
Published: (2025)

Mean-Field Bayesian Optimisation
by: Steinberg, Petar, et al.
Published: (2025)

Training Diverse Graph Experts for Ensembles: A Systematic Empirical Study
by: Deng, Gangda, et al.
Published: (2025)

Distributionally Robust Optimisation with Bayesian Ambiguity Sets
by: Dellaporta, Charita, et al.
Published: (2024)

Bayesian Optimistic Optimisation with Exponentially Decaying Regret
by: Tran-The, Hung, et al.
Published: (2021)

An Optimised Greedy-Weighted Ensemble Framework for Financial Loan Default Prediction
by: Nortey, Ezekiel Nii Noye, et al.
Published: (2026)

On Uniform, Bayesian, and PAC-Bayesian Deep Ensembles
by: Hauptvogel, Nick, et al.
Published: (2024)

Transferable Reward Learning by Dynamics-Agnostic Discriminator Ensemble
by: Luo, Fan-Ming, et al.
Published: (2022)

Trust Region-Based Bayesian Optimisation to Discover Diverse Solutions
by: Perera, Kokila Kasuni, et al.
Published: (2025)

Bayesian Optimization for Mixed-Variable Problems in the Natural Sciences
by: Zhang, Yuhao, et al.
Published: (2026)

Bayesian Optimisation: Which Constraints Matter?
by: Lin, Xietao Wang, et al.
Published: (2025)

Bayesian Optimisation Against Climate Change: Applications and Benchmarks
by: Hellan, Sigrid Passano, et al.
Published: (2023)

Sample-efficient Bayesian Optimisation Using Known Invariances
by: Brown, Theodore, et al.
Published: (2024)

Modeling Psychological Profiles in Volleyball via Mixed-Type Bayesian Networks
by: Iannario, Maria, et al.
Published: (2025)

Transfer Learning for Latent Variable Network Models
by: Jalan, Akhil, et al.
Published: (2024)

Towards E-Value Based Stopping Rules for Bayesian Deep Ensembles
by: Sommer, Emanuel, et al.
Published: (2026)

Principled Bayesian Optimisation in Collaboration with Human Experts
by: Xu, Wenjie, et al.
Published: (2024)

Scalable Structure Learning of Bayesian Networks by Learning Algorithm Ensembles
by: Liu, Shengcai, et al.
Published: (2025)

FedBEns: One-Shot Federated Learning based on Bayesian Ensemble
by: Talpini, Jacopo, et al.
Published: (2025)

The Impact of Variable Ordering on Bayesian Network Structure Learning
by: Kitson, Neville K, et al.
Published: (2022)

Learning Relevant Contextual Variables Within Bayesian Optimization
by: Martinelli, Julien, et al.
Published: (2023)

Multi-Task Learning for Metal Alloy Property Prediction: An Empirical Study of Negative Transfer and Mitigation Strategies
by: Kang, Sungwoo
Published: (2025)

To Stay or Not to Stay in the Pre-train Basin: Insights on Ensembling in Transfer Learning
by: Sadrtdinov, Ildus, et al.
Published: (2023)