SOTAVerified

Bayesian Optimisation

Expensive black-box functions are a common problem in many disciplines, including tuning the parameters of machine learning algorithms, robotics, and other engineering design problems. Bayesian Optimisation is a principled and efficient technique for the global optimisation of these functions. The idea behind Bayesian Optimisation is to place a prior distribution over the target function and then update that prior with a set of “true” observations of the target function by expensively evaluating it in order to produce a posterior predictive distribution. The posterior then informs where to make the next observation of the target function through the use of an acquisition function, which balances the exploitation of regions known to have good performance with the exploration of regions where there is little information about the function’s response.

Source: A Bayesian Approach for the Robust Optimisation of Expensive-to-Evaluate Functions

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 101–150 of 221 papers

TitleStatusHype
Preferential Bayesian optimisation with Skew Gaussian Processes—0
Process-constrained batch Bayesian optimisation—0
Rapid Bayesian optimisation for synthesis of short polymer fiber materials—0
Regret Bounds for Noise-Free Kernel-Based Bandits—0
Risk-Averse Bayes-Adaptive Reinforcement Learning—0
R-MBO: A Multi-surrogate Approach for Preference Incorporation in Multi-objective Bayesian Optimisation—0
Sample-Efficient Optimisation with Probabilistic Transformer Surrogates—0
Search Strategies for Self-driving Laboratories with Pending Experiments—0
Sequential Subspace Search for Functional Bayesian Optimization Incorporating Experimenter Intuition—0
Shaping of Magnetic Field Coils in Fusion Reactors using Bayesian Optimisation—0
Single and Multi-Objective Real-Time Optimisation of an Industrial Injection Moulding Process via a Bayesian Adaptive Design of Experiment Approach—0
Soft Reasoning: Navigating Solution Spaces in Large Language Models through Controlled Embedding Exploration—0
Some variation of COBRA in sequential learning setup—0
Sparse Spectrum Gaussian Process for Bayesian Optimization—0
Misspecification-robust likelihood-free inference in high dimensions—0
Stable Bayesian Optimisation via Direct Stability Quantification—0
Sub-linear Regret Bounds for Bayesian Optimisation in Unknown Search Spaces—0
Trading Convergence Rate with Computational Budget in High Dimensional Bayesian Optimization—0
Uncertainty Aware System Identification with Universal Policies—0
Uncovering Energy-Efficient Practices in Deep Learning Training: Preliminary Steps Towards Green AI—0
Unsupervised machine learning for data-driven rock mass classification: addressing limitations in existing systems using drilling data—0
What Makes an Effective Scalarising Function for Multi-Objective Bayesian Optimisation?—0
Will More Expressive Graph Neural Networks do Better on Generative Tasks?—0
Bayesian Search for Robust Optima—0
Wind Farm Layout Optimisation using Set Based Multi-objective Bayesian Optimisation—0
Adaptive Model Predictive Control by Learning Classifiers—0
Adjoint-aided inference of Gaussian process driven differential equations—0
Alternating Optimisation and Quadrature for Robust Control—0
Antifragile and Robust Heteroscedastic Bayesian Optimisation—0
Approximate Bayesian inference from noisy likelihoods with Gaussian process emulated MCMC—0
Approximate Bayesian Optimisation for Neural Networks—0
Approximate Neural Architecture Search via Operation Distribution Learning—0
Attacking Graph Classification via Bayesian Optimisation—0
A Two-Stage Bayesian Optimisation for Automatic Tuning of an Unscented Kalman Filter for Vehicle Sideslip Angle Estimation—0
Automated control and optimisation of laser driven ion acceleration—0
Automated Machine Learning on Big Data using Stochastic Algorithm Tuning—0
Automatic Clustering for Unsupervised Risk Diagnosis of Vehicle Driving for Smart Road—0
Automatic Tuning of Stochastic Gradient Descent with Bayesian Optimisation—0
Batch simulations and uncertainty quantification in Gaussian process surrogate approximate Bayesian computation—0
Bayesian Deep Learning for Interactive Community Question Answering—0
Bayesian functional optimisation with shape prior—0
Bayesian learning of feature spaces for multitasks problems—0
Bayesian Optimisation-Assisted Neural Network Training Technique for Radio Localisation—0
Bayesian Optimisation for a Biologically Inspired Population Neural Network—0
Bayesian Optimisation for Active Monitoring of Air Pollution—0
Bayesian Optimisation for Constrained Problems—0
Bayesian Optimisation for Machine Translation—0
Bayesian Optimisation for Mixed-Variable Inputs using Value Proposals—0
Bayesian Optimisation for Robust Model Predictive Control under Model Parameter Uncertainty—0
Bayesian Optimisation for Safe Navigation under Localisation Uncertainty—0
Show:102550
← PrevPage 3 of 5Next →

No leaderboard results yet.