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Bayesian Optimisation

21 papers with code · Methodology

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BoTorch: Programmable Bayesian Optimization in PyTorch

14 Oct 2019pytorch/botorch

Bayesian optimization provides sample-efficient global optimization for a broad range of applications, including automatic machine learning, molecular chemistry, and experimental design.

BAYESIAN OPTIMISATION

Batch Bayesian Optimization via Local Penalization

29 May 2015SheffieldML/GPyOpt

The approach assumes that the function of interest, $f$, is a Lipschitz continuous function.

BAYESIAN OPTIMISATION EFFICIENT EXPLORATION GAUSSIAN PROCESSES

Tuning Hyperparameters without Grad Students: Scalable and Robust Bayesian Optimisation with Dragonfly

15 Mar 2019dragonfly/dragonfly

We compare Dragonfly to a suite of other packages and algorithms for global optimisation and demonstrate that when the above methods are integrated, they enable significant improvements in the performance of BO.

BAYESIAN OPTIMISATION

GPflowOpt: A Bayesian Optimization Library using TensorFlow

10 Nov 2017GPflow/GPflowOpt

A novel Python framework for Bayesian optimization known as GPflowOpt is introduced.

BAYESIAN OPTIMISATION GAUSSIAN PROCESSES

Neural Architecture Search with Bayesian Optimisation and Optimal Transport

NeurIPS 2018 kirthevasank/nasbot

A common use case for BO in machine learning is model selection, where it is not possible to analytically model the generalisation performance of a statistical model, and we resort to noisy and expensive training and validation procedures to choose the best model.

BAYESIAN OPTIMISATION MODEL SELECTION NEURAL ARCHITECTURE SEARCH

Effective Estimation of Deep Generative Language Models

17 Apr 2019tom-pelsmaeker/deep-generative-lm

We concentrate on one such model, the variational auto-encoder, which we argue is an important building block in hierarchical probabilistic models of language.

BAYESIAN OPTIMISATION LANGUAGE MODELLING

Fast Information-theoretic Bayesian Optimisation

ICML 2018 rubinxin/FITBO

Information-theoretic Bayesian optimisation techniques have demonstrated state-of-the-art performance in tackling important global optimisation problems.

BAYESIAN OPTIMISATION

BayesOpt Adversarial Attack

ICLR 2020 rubinxin/BayesOpt_Attack

Black-box adversarial attacks require a large number of attempts before finding successful adversarial examples that are visually indistinguishable from the original input.

ADVERSARIAL ATTACK BAYESIAN OPTIMISATION DIMENSIONALITY REDUCTION MODEL SELECTION

Gaussian Process Priors for Dynamic Paired Comparison Modelling

20 Feb 2019martiningram/paired-comparison-gp-laplace

Dynamic paired comparison models, such as Elo and Glicko, are frequently used for sports prediction and ranking players or teams.

BAYESIAN INFERENCE BAYESIAN OPTIMISATION

Bayesian optimisation for fast approximate inference in state-space models with intractable likelihoods

23 Jun 2015compops/gpo-smc-abc

We consider the problem of approximate Bayesian parameter inference in non-linear state-space models with intractable likelihoods.

BAYESIAN OPTIMISATION