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qLogEI #1936
qLogEI #1936
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This pull request was exported from Phabricator. Differential Revision: D47439148 |
Codecov Report
@@ Coverage Diff @@
## main #1936 +/- ##
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Coverage 99.94% 99.94%
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Files 176 177 +1
Lines 15500 15591 +91
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+ Hits 15492 15583 +91
Misses 8 8
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Summary: Pull Request resolved: pytorch#1936 This commit introduces `qLogExpectedImprovement` (`qLogEI`), which computes the logarithm of a smooth approximation to the regular EI utility. As EI is known to suffer from vanishing gradients, especially for challenging, constrained, or high-dimensional problems, using `qLogEI` can lead to significant optimization improvements. Differential Revision: D47439148 fbshipit-source-id: 678832c31e6746fb748803d956ee3d0365a39d82
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This pull request was exported from Phabricator. Differential Revision: D47439148 |
Summary: Pull Request resolved: pytorch#1936 This commit introduces `qLogExpectedImprovement` (`qLogEI`), which computes the logarithm of a smooth approximation to the regular EI utility. As EI is known to suffer from vanishing gradients, especially for challenging, constrained, or high-dimensional problems, using `qLogEI` can lead to significant optimization improvements. Differential Revision: D47439148 fbshipit-source-id: 5d4e4bff431332659684f0831bdc586b36d7d973
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This pull request was exported from Phabricator. Differential Revision: D47439148 |
Summary: Pull Request resolved: pytorch#1936 This commit introduces `qLogExpectedImprovement` (`qLogEI`), which computes the logarithm of a smooth approximation to the regular EI utility. As EI is known to suffer from vanishing gradients, especially for challenging, constrained, or high-dimensional problems, using `qLogEI` can lead to significant optimization improvements. Differential Revision: D47439148 fbshipit-source-id: 6df3fe90382f465d5f99c36708e38a87b89aa8bd
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This pull request was exported from Phabricator. Differential Revision: D47439148 |
Summary: Pull Request resolved: pytorch#1936 This commit introduces `qLogExpectedImprovement` (`qLogEI`), which computes the logarithm of a smooth approximation to the regular EI utility. As EI is known to suffer from vanishing gradients, especially for challenging, constrained, or high-dimensional problems, using `qLogEI` can lead to significant optimization improvements. Differential Revision: D47439148 fbshipit-source-id: c10847bbcbb817c79b63f61b4ffe9ea716adbba7
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This pull request was exported from Phabricator. Differential Revision: D47439148 |
Summary: Pull Request resolved: pytorch#1936 This commit introduces `qLogExpectedImprovement` (`qLogEI`), which computes the logarithm of a smooth approximation to the regular EI utility. As EI is known to suffer from vanishing gradients, especially for challenging, constrained, or high-dimensional problems, using `qLogEI` can lead to significant optimization improvements. Differential Revision: D47439148 fbshipit-source-id: 399d74065f1f1afa190193989d1d963a9c7b6f38
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This pull request was exported from Phabricator. Differential Revision: D47439148 |
Summary: Pull Request resolved: pytorch#1936 This commit introduces `qLogExpectedImprovement` (`qLogEI`), which computes the logarithm of a smooth approximation to the regular EI utility. As EI is known to suffer from vanishing gradients, especially for challenging, constrained, or high-dimensional problems, using `qLogEI` can lead to significant optimization improvements. Differential Revision: D47439148 fbshipit-source-id: 6c6d23d0d102e91ed4d3607b69724dbc8a80595a
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This pull request was exported from Phabricator. Differential Revision: D47439148 |
Summary: Pull Request resolved: pytorch#1936 This commit introduces `qLogExpectedImprovement` (`qLogEI`), which computes the logarithm of a smooth approximation to the regular EI utility. As EI is known to suffer from vanishing gradients, especially for challenging, constrained, or high-dimensional problems, using `qLogEI` can lead to significant optimization improvements. Differential Revision: D47439148 fbshipit-source-id: 3d0545796ec8087d0b301f1d13ba38cad29661e9
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This pull request was exported from Phabricator. Differential Revision: D47439148 |
Summary: Pull Request resolved: pytorch#1936 This commit introduces `qLogExpectedImprovement` (`qLogEI`), which computes the logarithm of a smooth approximation to the regular EI utility. As EI is known to suffer from vanishing gradients, especially for challenging, constrained, or high-dimensional problems, using `qLogEI` can lead to significant optimization improvements. Differential Revision: https://internalfb.com/D47439148 fbshipit-source-id: ff5ec11526a8b403509ae9c5c34d76e869b310fd
Summary: Pull Request resolved: pytorch#1936 This commit introduces `qLogExpectedImprovement` (`qLogEI`), which computes the logarithm of a smooth approximation to the regular EI utility. As EI is known to suffer from vanishing gradients, especially for challenging, constrained, or high-dimensional problems, using `qLogEI` can lead to significant optimization improvements. Differential Revision: D47439148 fbshipit-source-id: 568aebb5a6338c61c908872d6a131479b6587577
This pull request was exported from Phabricator. Differential Revision: D47439148 |
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Summary: Pull Request resolved: pytorch#1936 This commit introduces `qLogExpectedImprovement` (`qLogEI`), which computes the logarithm of a smooth approximation to the regular EI utility. As EI is known to suffer from vanishing gradients, especially for challenging, constrained, or high-dimensional problems, using `qLogEI` can lead to significant optimization improvements. Differential Revision: D47439148 fbshipit-source-id: 76bb795eb277a557e366bed1c3841c332f3d7993
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This pull request was exported from Phabricator. Differential Revision: D47439148 |
Summary: Pull Request resolved: pytorch#1936 This commit introduces `qLogExpectedImprovement` (`qLogEI`), which computes the logarithm of a smooth approximation to the regular EI utility. As EI is known to suffer from vanishing gradients, especially for challenging, constrained, or high-dimensional problems, using `qLogEI` can lead to significant optimization improvements. Differential Revision: D47439148 fbshipit-source-id: 4982962bc0dea3f0768d52fabdbabffad9c1d187
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This pull request was exported from Phabricator. Differential Revision: D47439148 |
Summary: Pull Request resolved: pytorch#1936 This commit introduces `qLogExpectedImprovement` (`qLogEI`), which computes the logarithm of a smooth approximation to the regular EI utility. As EI is known to suffer from vanishing gradients, especially for challenging, constrained, or high-dimensional problems, using `qLogEI` can lead to significant optimization improvements. Differential Revision: https://internalfb.com/D47439148 fbshipit-source-id: e3c3ba6f4d1c33f60f09b61dcf8552613f7fc513
Summary: Pull Request resolved: pytorch#1936 This commit introduces `qLogExpectedImprovement` (`qLogEI`), which computes the logarithm of a smooth approximation to the regular EI utility. As EI is known to suffer from vanishing gradients, especially for challenging, constrained, or high-dimensional problems, using `qLogEI` can lead to significant optimization improvements. Differential Revision: https://internalfb.com/D47439148 fbshipit-source-id: bdbe8f70865e4c6d3772d33a34404d3843d93d0d
Summary: Pull Request resolved: pytorch#1936 This commit introduces `qLogExpectedImprovement` (`qLogEI`), which computes the logarithm of a smooth approximation to the regular EI utility. As EI is known to suffer from vanishing gradients, especially for challenging, constrained, or high-dimensional problems, using `qLogEI` can lead to significant optimization improvements. Differential Revision: D47439148 fbshipit-source-id: 01eba81699f6c268375e0cb3ab2fc04068aed8fc
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This pull request was exported from Phabricator. Differential Revision: D47439148 |
Summary: Pull Request resolved: pytorch#1936 This commit introduces `qLogExpectedImprovement` (`qLogEI`), which computes the logarithm of a smooth approximation to the regular EI utility. As EI is known to suffer from vanishing gradients, especially for challenging, constrained, or high-dimensional problems, using `qLogEI` can lead to significant optimization improvements. Differential Revision: D47439148 fbshipit-source-id: 9451f1bb7754033a7c06efdcad912e9b87c299ed
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This pull request was exported from Phabricator. Differential Revision: D47439148 |
Summary: Pull Request resolved: pytorch#1936 This commit introduces `qLogExpectedImprovement` (`qLogEI`), which computes the logarithm of a smooth approximation to the regular EI utility. As EI is known to suffer from vanishing gradients, especially for challenging, constrained, or high-dimensional problems, using `qLogEI` can lead to significant optimization improvements. Differential Revision: https://internalfb.com/D47439148 fbshipit-source-id: 03731c8a85f865286bafdb7c26c7b9e4a118020a
Summary: Pull Request resolved: pytorch#1936 This commit introduces `qLogExpectedImprovement` (`qLogEI`), which computes the logarithm of a smooth approximation to the regular EI utility. As EI is known to suffer from vanishing gradients, especially for challenging, constrained, or high-dimensional problems, using `qLogEI` can lead to significant optimization improvements. Reviewed By: Balandat Differential Revision: D47439148 fbshipit-source-id: a98ff8f5e3ea9070640a0c0dfadbcc5344e06299
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This pull request was exported from Phabricator. Differential Revision: D47439148 |
Summary: Pull Request resolved: pytorch#1936 This commit introduces `qLogExpectedImprovement` (`qLogEI`), which computes the logarithm of a smooth approximation to the regular EI utility. As EI is known to suffer from vanishing gradients, especially for challenging, constrained, or high-dimensional problems, using `qLogEI` can lead to significant optimization improvements. Reviewed By: Balandat Differential Revision: D47439148 fbshipit-source-id: 161078f46e9966dcf5eabbfbc943fe91c97682b5
754f015
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Compare
This pull request was exported from Phabricator. Differential Revision: D47439148 |
Summary: Pull Request resolved: pytorch#1936 This commit introduces `qLogExpectedImprovement` (`qLogEI`), which computes the logarithm of a smooth approximation to the regular EI utility. As EI is known to suffer from vanishing gradients, especially for challenging, constrained, or high-dimensional problems, using `qLogEI` can lead to significant optimization improvements. Differential Revision: https://internalfb.com/D47439148 fbshipit-source-id: da65264ee92f3d36cd39dca9a31bd4645f9b4b21
Summary: Pull Request resolved: pytorch#1936 This commit introduces `qLogExpectedImprovement` (`qLogEI`), which computes the logarithm of a smooth approximation to the regular EI utility. As EI is known to suffer from vanishing gradients, especially for challenging, constrained, or high-dimensional problems, using `qLogEI` can lead to significant optimization improvements. Reviewed By: Balandat Differential Revision: D47439148 fbshipit-source-id: 400c30e326e3a0a5db192be0800d691b8dbf1c1d
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This pull request was exported from Phabricator. Differential Revision: D47439148 |
This pull request has been merged in 50bcf95. |
Summary: This commit introduces
qLogExpectedImprovement
(qLogEI
), which computes the logarithm of a smooth approximation to the regular EI utility. As EI is known to suffer from vanishing gradients, especially for challenging, constrained, or high-dimensional problems, usingqLogEI
can lead to significant optimization improvements.Differential Revision: D47439148