Results 21 to 30 of about 288,690 (232)
Warm starting Bayesian optimization [PDF]
2016 Winter Simulation Conference (WSC), 2016 To Appear in the Proc.
Matthias Poloczek +2 more
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Triangulation Candidates for Bayesian Optimization
Advances in Neural Information Processing Systems 35, 2022 Bayesian optimization involves "inner optimization" over a new-data acquisition criterion which is non-convex/highly multi-modal, may be non-differentiable, or may otherwise thwart local numerical optimizers. In such cases it is common to replace continuous search with a discrete one over random candidates.
Robert B. Gramacy +2 more
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Bayesian Optimization with Local Search [PDF]
, 2020 Global optimization finds applications in a wide range of real world problems. The multi-start methods are a popular class of global optimization techniques, which are based on the ideas of conducting local searches at multiple starting points. In this work we propose a new multi-start algorithm where the starting points are determined in a Bayesian ...
Yuzhou Gao, Tengchao Yu, Jinglai Li
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On Batch Bayesian Optimization
CoRR, 2019 All of Bayesian Nonparametrics workshop, Neural Information Processing Systems ...
Sayak Ray Chowdhury, Aditya Gopalan
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Bayesian Optimization Based on K-Optimality [PDF]
Entropy, 2018 Bayesian optimization (BO) based on the Gaussian process (GP) surrogate model has attracted extensive attention in the field of optimization and design of experiments (DoE). It usually faces two problems: the unstable GP prediction due to the ill-conditioned Gram matrix of the kernel and the difficulty of determining the trade-off parameter between ...
Liang Yan 0003 +3 more
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Bayesian Optimization for Conformer Generation [PDF]
Journal of Cheminformatics, 2018 Generating low-energy molecular conformers is a key task for many areas of computational chemistry, molecular modeling and cheminformatics. Most current conformer generation methods primarily focus on generating geometrically diverse conformers rather than finding the most probable or energetically lowest minima.
Lucian Chan +2 more
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FEBS Open Bio, EarlyView.This protocol paper outlines methods to establish the success of a time‐resolved serial crystallographic experiment, by means of statistical analysis of timepoint data in reciprocal space and models in real space. We show how to amplify the signal from excited states to visualise structural changes in successful experiments.
Jake Hill +4 more
wiley +1 more source
Bayesian Optimization for Optimizing Retrieval Systems [PDF]
Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining, 2018 The effectiveness of information retrieval systems heavily depends on a large number of hyperparameters that need to be tuned. Hyperparameters range from the choice of different system components, e.g., stopword lists, stemming methods, or retrieval models, to model parameters, such as k1 and b in BM25, or the number of query expansion terms.
Dan Li 0015, Evangelos Kanoulas
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FEBS Open Bio, EarlyView.Evolutionary analysis across 32 placental mammals identified positive selection at residues H148 and W149 in the immune receptor FcγR1. Ancestral reconstruction combined with molecular dynamics simulations reveals how these mutations may influence receptor structure and dynamics, providing insight into the evolution of antibody recognition and immune ...
David A. Young +7 more
wiley +1 more source
Bayesian Optimization in Bioprocess Engineering—Where Do We Stand Today? [PDF]
Biotechnology and BioengineeringFlorian Gisperg +2 more
exaly +2 more sources