Update the default SingleTaskGP prior #2449
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Summary: X-link: pytorch/botorch#2449 See title Differential Revision: D60080819
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Summary: X-link: facebook/Ax#2610 Pull Request resolved: pytorch#2449 See title Differential Revision: D60080819
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Summary: X-link: pytorch/botorch#2449 Update of the default hyperparameter priors for the SingleTaskGP. Switch from the conventional Scale-Matern kernel with Gamma(3, 6) lengthscale prior is substituted for an RBF Kernel (without a ScaleKernel), and a change from the high-noise Gamma(1.1, 0.05) noise prior of the GaussianLikelihood to a LogNormal prior that prefers lower values. The change is made in accordance with the findings of [1]. The change is made to improve the out-of-the-box performance of the BoTorch models on high-dimensional problems. [1] Carl Hvarfner, Erik Orm Hellsten, Luigi Nardi. _Vanilla Bayesian Optimization Performs Great in High Dimensions_. ICML, 2024. Reviewed By: saitcakmak Differential Revision: D60080819
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Summary: Pull Request resolved: pytorch#2449 Update of the default hyperparameter priors for the SingleTaskGP. Switch from the conventional Scale-Matern kernel with Gamma(3, 6) lengthscale prior is substituted for an RBF Kernel (without a ScaleKernel), and a change from the high-noise Gamma(1.1, 0.05) noise prior of the GaussianLikelihood to a LogNormal prior that prefers lower values. The change is made in accordance with the findings of [1]. The change is made to improve the out-of-the-box performance of the BoTorch models on high-dimensional problems. [1] Carl Hvarfner, Erik Orm Hellsten, Luigi Nardi. _Vanilla Bayesian Optimization Performs Great in High Dimensions_. ICML, 2024. Reviewed By: saitcakmak Differential Revision: D60080819
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Summary: X-link: facebook/Ax#2610 Pull Request resolved: pytorch#2449 Update of the default hyperparameter priors for the SingleTaskGP. Switch from the conventional Scale-Matern kernel with Gamma(3, 6) lengthscale prior is substituted for an RBF Kernel (without a ScaleKernel), and a change from the high-noise Gamma(1.1, 0.05) noise prior of the GaussianLikelihood to a LogNormal prior that prefers lower values. The change is made in accordance with the findings of [1]. The change is made to improve the out-of-the-box performance of the BoTorch models on high-dimensional problems. [1] Carl Hvarfner, Erik Orm Hellsten, Luigi Nardi. _Vanilla Bayesian Optimization Performs Great in High Dimensions_. ICML, 2024. Reviewed By: saitcakmak Differential Revision: D60080819
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Summary: X-link: facebook/Ax#2610 Pull Request resolved: pytorch#2449 Update of the default hyperparameter priors for the SingleTaskGP. Switch from the conventional Scale-Matern kernel with Gamma(3, 6) lengthscale prior is substituted for an RBF Kernel (without a ScaleKernel), and a change from the high-noise Gamma(1.1, 0.05) noise prior of the GaussianLikelihood to a LogNormal prior that prefers lower values. The change is made in accordance with the findings of [1]. The change is made to improve the out-of-the-box performance of the BoTorch models on high-dimensional problems. [1] Carl Hvarfner, Erik Orm Hellsten, Luigi Nardi. _Vanilla Bayesian Optimization Performs Great in High Dimensions_. ICML, 2024. Reviewed By: saitcakmak Differential Revision: D60080819
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Summary: Pull Request resolved: facebook#2610 X-link: pytorch/botorch#2449 Update of the default hyperparameter priors for the SingleTaskGP. Switch from the conventional Scale-Matern kernel with Gamma(3, 6) lengthscale prior is substituted for an RBF Kernel (without a ScaleKernel), and a change from the high-noise Gamma(1.1, 0.05) noise prior of the GaussianLikelihood to a LogNormal prior that prefers lower values. The change is made in accordance with the findings of [1]. The change is made to improve the out-of-the-box performance of the BoTorch models on high-dimensional problems. [1] Carl Hvarfner, Erik Orm Hellsten, Luigi Nardi. _Vanilla Bayesian Optimization Performs Great in High Dimensions_. ICML, 2024. Reviewed By: saitcakmak Differential Revision: D60080819
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Summary: X-link: facebook/Ax#2610 Pull Request resolved: pytorch#2449 Update of the default hyperparameter priors for the SingleTaskGP. Switch from the conventional Scale-Matern kernel with Gamma(3, 6) lengthscale prior is substituted for an RBF Kernel (without a ScaleKernel), and a change from the high-noise Gamma(1.1, 0.05) noise prior of the GaussianLikelihood to a LogNormal prior that prefers lower values. The change is made in accordance with the findings of [1]. The change is made to improve the out-of-the-box performance of the BoTorch models on high-dimensional problems. [1] Carl Hvarfner, Erik Orm Hellsten, Luigi Nardi. _Vanilla Bayesian Optimization Performs Great in High Dimensions_. ICML, 2024. Reviewed By: saitcakmak Differential Revision: D60080819
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Codecov ReportAll modified and coverable lines are covered by tests ✅
Additional details and impacted files@@ Coverage Diff @@
## main #2449 +/- ##
=======================================
Coverage 99.98% 99.98%
=======================================
Files 190 190
Lines 16740 16741 +1
=======================================
+ Hits 16738 16739 +1
Misses 2 2 ☔ View full report in Codecov by Sentry. |
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Summary: X-link: facebook/Ax#2610 Pull Request resolved: pytorch#2449 Update of the default hyperparameter priors for the SingleTaskGP. Switch from the conventional Scale-Matern kernel with Gamma(3, 6) lengthscale prior is substituted for an RBF Kernel (without a ScaleKernel), and a change from the high-noise Gamma(1.1, 0.05) noise prior of the GaussianLikelihood to a LogNormal prior that prefers lower values. The change is made in accordance with the findings of [1]. The change is made to improve the out-of-the-box performance of the BoTorch models on high-dimensional problems. [1] Carl Hvarfner, Erik Orm Hellsten, Luigi Nardi. _Vanilla Bayesian Optimization Performs Great in High Dimensions_. ICML, 2024. Reviewed By: saitcakmak Differential Revision: D60080819
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Summary: X-link: facebook/Ax#2610 Pull Request resolved: pytorch#2449 Update of the default hyperparameter priors for the SingleTaskGP. Switch from the conventional Scale-Matern kernel with Gamma(3, 6) lengthscale prior is substituted for an RBF Kernel (without a ScaleKernel), and a change from the high-noise Gamma(1.1, 0.05) noise prior of the GaussianLikelihood to a LogNormal prior that prefers lower values. The change is made in accordance with the findings of [1]. The change is made to improve the out-of-the-box performance of the BoTorch models on high-dimensional problems. [1] Carl Hvarfner, Erik Orm Hellsten, Luigi Nardi. _Vanilla Bayesian Optimization Performs Great in High Dimensions_. ICML, 2024. Reviewed By: saitcakmak Differential Revision: D60080819
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Summary: X-link: facebook/Ax#2610 Pull Request resolved: pytorch#2449 Update of the default hyperparameter priors for the SingleTaskGP. Switch from the conventional Scale-Matern kernel with Gamma(3, 6) lengthscale prior is substituted for an RBF Kernel (without a ScaleKernel), and a change from the high-noise Gamma(1.1, 0.05) noise prior of the GaussianLikelihood to a LogNormal prior that prefers lower values. The change is made in accordance with the findings of [1]. The change is made to improve the out-of-the-box performance of the BoTorch models on high-dimensional problems. [1] Carl Hvarfner, Erik Orm Hellsten, Luigi Nardi. _Vanilla Bayesian Optimization Performs Great in High Dimensions_. ICML, 2024. Reviewed By: saitcakmak Differential Revision: D60080819
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Summary: X-link: facebook/Ax#2610 Pull Request resolved: pytorch#2449 Update of the default hyperparameter priors for the SingleTaskGP. Switch from the conventional Scale-Matern kernel with Gamma(3, 6) lengthscale prior is substituted for an RBF Kernel (without a ScaleKernel), and a change from the high-noise Gamma(1.1, 0.05) noise prior of the GaussianLikelihood to a LogNormal prior that prefers lower values. The change is made in accordance with the findings of [1]. The change is made to improve the out-of-the-box performance of the BoTorch models on high-dimensional problems. [1] Carl Hvarfner, Erik Orm Hellsten, Luigi Nardi. _Vanilla Bayesian Optimization Performs Great in High Dimensions_. ICML, 2024. Reviewed By: saitcakmak Differential Revision: D60080819
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Summary: Pull Request resolved: facebook#2610 X-link: pytorch/botorch#2449 Update of the default hyperparameter priors for the SingleTaskGP. Switch from the conventional Scale-Matern kernel with Gamma(3, 6) lengthscale prior is substituted for an RBF Kernel (without a ScaleKernel), and a change from the high-noise Gamma(1.1, 0.05) noise prior of the GaussianLikelihood to a LogNormal prior that prefers lower values. The change is made in accordance with the findings of [1]. The change is made to improve the out-of-the-box performance of the BoTorch models on high-dimensional problems. [1] Carl Hvarfner, Erik Orm Hellsten, Luigi Nardi. _Vanilla Bayesian Optimization Performs Great in High Dimensions_. ICML, 2024. Reviewed By: saitcakmak Differential Revision: D60080819
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Summary: Pull Request resolved: facebook#2610 X-link: pytorch/botorch#2449 Update of the default hyperparameter priors for the SingleTaskGP. Switch from the conventional Scale-Matern kernel with Gamma(3, 6) lengthscale prior is substituted for an RBF Kernel (without a ScaleKernel), and a change from the high-noise Gamma(1.1, 0.05) noise prior of the GaussianLikelihood to a LogNormal prior that prefers lower values. The change is made in accordance with the findings of [1]. The change is made to improve the out-of-the-box performance of the BoTorch models on high-dimensional problems. [1] Carl Hvarfner, Erik Orm Hellsten, Luigi Nardi. _Vanilla Bayesian Optimization Performs Great in High Dimensions_. ICML, 2024. Reviewed By: saitcakmak Differential Revision: D60080819
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Summary: X-link: facebook/Ax#2610 Pull Request resolved: pytorch#2449 Update of the default hyperparameter priors for the SingleTaskGP. Switch from the conventional Scale-Matern kernel with Gamma(3, 6) lengthscale prior is substituted for an RBF Kernel (without a ScaleKernel), and a change from the high-noise Gamma(1.1, 0.05) noise prior of the GaussianLikelihood to a LogNormal prior that prefers lower values. The change is made in accordance with the findings of [1]. The change is made to improve the out-of-the-box performance of the BoTorch models on high-dimensional problems. [1] Carl Hvarfner, Erik Orm Hellsten, Luigi Nardi. _Vanilla Bayesian Optimization Performs Great in High Dimensions_. ICML, 2024. Reviewed By: saitcakmak Differential Revision: D60080819
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Summary: X-link: facebook/Ax#2610 Pull Request resolved: pytorch#2449 Update of the default hyperparameter priors for the SingleTaskGP. Switch from the conventional Scale-Matern kernel with Gamma(3, 6) lengthscale prior is substituted for an RBF Kernel (without a ScaleKernel), and a change from the high-noise Gamma(1.1, 0.05) noise prior of the GaussianLikelihood to a LogNormal prior that prefers lower values. The change is made in accordance with the findings of [1]. The change is made to improve the out-of-the-box performance of the BoTorch models on high-dimensional problems. [1] Carl Hvarfner, Erik Orm Hellsten, Luigi Nardi. _Vanilla Bayesian Optimization Performs Great in High Dimensions_. ICML, 2024. Reviewed By: saitcakmak Differential Revision: D60080819
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Summary: Pull Request resolved: #2610 X-link: pytorch/botorch#2449 Update of the default hyperparameter priors for the SingleTaskGP. Switch from the conventional Scale-Matern kernel with Gamma(3, 6) lengthscale prior is substituted for an RBF Kernel (without a ScaleKernel), and a change from the high-noise Gamma(1.1, 0.05) noise prior of the GaussianLikelihood to a LogNormal prior that prefers lower values. The change is made in accordance with the findings of [1]. The change is made to improve the out-of-the-box performance of the BoTorch models on high-dimensional problems. [1] Carl Hvarfner, Erik Orm Hellsten, Luigi Nardi. _Vanilla Bayesian Optimization Performs Great in High Dimensions_. ICML, 2024. Reviewed By: dme65, saitcakmak Differential Revision: D60080819 fbshipit-source-id: d55ff91dee9949cbd7f5828531644fc001cb3e22
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Update of the default hyperparameter priors for the SingleTaskGP.
Full discussion here
Switch from the conventional Scale-Matern kernel with Gamma(3, 6) lengthscale prior is substituted for an RBF Kernel (without a ScaleKernel), and a change from the high-noise Gamma(1.1, 0.05) noise prior of the GaussianLikelihood to a LogNormal prior that prefers lower values. The change is made in accordance with the findings of [1].
The change is made to improve the out-of-the-box performance of the BoTorch models on high-dimensional problems.
[1] Carl Hvarfner, Erik Orm Hellsten, Luigi Nardi. Vanilla Bayesian Optimization Performs Great in High Dimensions. ICML, 2024.