Cover Image

Sample-efficient Bayesian Optimisation Using Known Invariances

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Brown, Theodore, Cioba, Alexandru, Bogunovic, Ilija
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

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

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

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

REDUCR: Robust Data Downsampling Using Class Priority Reweighting
by: Bankes, William, et al.
Published: (2023)

Adversarially Robust Decision Transformer
by: Tang, Xiaohang, et al.
Published: (2024)

wd1: Weighted Policy Optimization for Reasoning in Diffusion Language Models
by: Tang, Xiaohang, et al.
Published: (2025)

Right Now, Wrong Then: Non-Stationary Direct Preference Optimization under Preference Drift
by: Son, Seongho, et al.
Published: (2024)

No-Regret Linear Bandits under Gap-Adjusted Misspecification
by: Liu, Chong, et al.
Published: (2025)

Synthetic Data is Sufficient for Zero-Shot Visual Generalization from Offline Data
by: Güzel, Ahmet H., et al.
Published: (2025)

Distributionally Robust Model-based Reinforcement Learning with Large State Spaces
by: Ramesh, Shyam Sundhar, et al.
Published: (2023)

RSPO: Regularized Self-Play Alignment of Large Language Models
by: Tang, Xiaohang, et al.
Published: (2025)

Sample Efficient Preference Alignment in LLMs via Active Exploration
by: Mehta, Viraj, et al.
Published: (2023)

DNN-Based Topology Optimisation: Spatial Invariance and Neural Tangent Kernel
by: Dupuis, Benjamin, et al.
Published: (2021)

PROSAC: Provably Safe Certification for Machine Learning Models under Adversarial Attacks
by: Feng, Chen, et al.
Published: (2024)

PROWL: Prioritized Regret-Driven Optimization for World Model Learning
by: Güzel, Ahmet H., et al.
Published: (2026)

LLM-WikiRace Benchmark: How Far Can LLMs Plan over Real-World Knowledge Graphs?
by: Ziomek, Juliusz, et al.
Published: (2026)

Robust Multi-Objective Controlled Decoding of Large Language Models
by: Son, Seongho, et al.
Published: (2025)

Sample-Efficient Optimisation over the Outputs of Generative Models
by: Willis, Samuel, et al.
Published: (2025)

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

On Almost Surely Safe Alignment of Large Language Models at Inference-Time
by: Ji, Xiaotong, et al.
Published: (2025)

GDSD: Reinforcement Learning as Guided Denoiser Self-Distillation for Diffusion Language Models
by: Tang, Xiaohang, et al.
Published: (2026)

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

Bayesian Optimization of Partially Known Systems using Hybrid Models
by: Cramer, Eike, et al.
Published: (2026)

Bayesian Invariance Modeling of Multi-Environment Data
by: Wu, Luhuan, et al.
Published: (2025)

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

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)

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

Group Robust Preference Optimization in Reward-free RLHF
by: Ramesh, Shyam Sundhar, et al.
Published: (2024)

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

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

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

Sample-efficient neural likelihood-free Bayesian inference of implicit HMMs
by: Ghosh, Sanmitra, et al.
Published: (2024)

Sample Complexity Bounds for Estimating Probability Divergences under Invariances
by: Tahmasebi, Behrooz, et al.
Published: (2023)

The Exact Sample Complexity Gain from Invariances for Kernel Regression
by: Tahmasebi, Behrooz, et al.
Published: (2023)

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

Imagined Autocurricula
by: Güzel, Ahmet H., et al.
Published: (2025)

Connecting the Dots: Is Mode-Connectedness the Key to Feasible Sample-Based Inference in Bayesian Neural Networks?
by: Sommer, Emanuel, et al.
Published: (2024)

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

MONGOOSE: Path-wise Smooth Bayesian Optimisation via Meta-learning
by: Yang, Adam X., et al.
Published: (2023)