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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

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Showing 51–100 of 221 papers

TitleStatusHype
Antifragile and Robust Heteroscedastic Bayesian Optimisation—0
Bayesian optimisation of large-scale photonic reservoir computers—0
Bayesian optimisation under uncertain inputs—0
Bayesian Optimisation vs. Input Uncertainty Reduction—0
Bayesian Optimisation with Formal Guarantees—0
Bayesian Optimisation with Gaussian Processes for Premise Selection—0
Automatic Tuning of Stochastic Gradient Descent with Bayesian Optimisation—0
Bayesian Optimistic Optimisation with Exponentially Decaying Regret—0
Inducing Point Allocation for Sparse Gaussian Processes in High-Throughput Bayesian Optimisation—0
Bayesian Optimization in AlphaGo—0
Bayesian Policy Reuse—0
Bayesian Quantile and Expectile Optimisation—0
Large Language Models for Human-Machine Collaborative Particle Accelerator Tuning through Natural Language—0
Bayesian Optimisation for Active Monitoring of Air Pollution—0
Bayesian Optimisation for a Biologically Inspired Population Neural Network—0
High-Dimensional Bayesian Optimisation with Large-Scale Constraints -- An Application to Aeroelastic Tailoring—0
Hidden Markov Model: Tutorial—0
Heteroscedastic Treed Bayesian Optimisation—0
High Dimensional Bayesian Optimisation and Bandits via Additive Models—0
Impact of HPO on AutoML Forecasting Ensembles—0
Large Language Models Orchestrating Structured Reasoning Achieve Kaggle Grandmaster Level—0
Bayesian learning of feature spaces for multitasks problems—0
Cost-aware Multi-objective Bayesian optimisation—0
Contextual Causal Bayesian Optimisation—0
GLASSES: Relieving The Myopia Of Bayesian Optimisation—0
Graph Agnostic Causal Bayesian Optimisation—0
Counterfactual Explanations for Arbitrary Regression Models—0
Covariance Function Pre-Training with m-Kernels for Accelerated Bayesian Optimisation—0
Choice functions based multi-objective Bayesian optimisation—0
Delayed Feedback in Kernel Bandits—0
Detecting COVID-19 from Breathing and Coughing Sounds using Deep Neural Networks—0
Bayesian Optimisation-Assisted Neural Network Training Technique for Radio Localisation—0
Bayesian functional optimisation with shape prior—0
Developmental Bayesian Optimization of Black-Box with Visual Similarity-Based Transfer Learning—0
Differential Evolution and Bayesian Optimisation for Hyper-Parameter Selection in Mixed-Signal Neuromorphic Circuits Applied to UAV Obstacle Avoidance—0
Dimensionality Reduction Techniques for Global Bayesian Optimisation—0
Bayesian Optimisation for Constrained Problems—0
Cell-Free Data Power Control Via Scalable Multi-Objective Bayesian Optimisation—0
Attacking Graph Classification via Bayesian Optimisation—0
'In-Between' Uncertainty in Bayesian Neural Networks—0
Efficient acquisition rules for model-based approximate Bayesian computation—0
Bayesian Optimisation for Machine Translation—0
Bayesian Optimisation for Mixed-Variable Inputs using Value Proposals—0
Information-theoretic Inducing Point Placement for High-throughput Bayesian Optimisation—0
Bayesian Deep Learning for Interactive Community Question Answering—0
Alternating Optimisation and Quadrature for Robust Control—0
Bayesian Optimisation for Safe Navigation under Localisation Uncertainty—0
Fast Model-based Policy Search for Universal Policy Networks—0
Graph-enabled Reinforcement Learning for Time Series Forecasting with Adaptive Intelligence—0
BOP-Elites, a Bayesian Optimisation algorithm for Quality-Diversity search—0
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