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Fix a bug for SVGP regression with minibatch traning #148
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added 2 commits
January 25, 2019 10:28
Remove the dependency on broadcast_w_samples operators in RBF and Linear kernel.
Codecov Report
@@ Coverage Diff @@
## develop #148 +/- ##
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+ Coverage 85.1% 85.19% +0.08%
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Files 77 78 +1
Lines 3814 3850 +36
Branches 653 654 +1
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+ Hits 3246 3280 +34
- Misses 375 376 +1
- Partials 193 194 +1
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|
meissnereric
approved these changes
Jan 25, 2019
| @@ -95,7 +95,7 @@ def compute(self, F, variables): | |||
| logL = logL + F.sum(F.sum(F.square(LinvKuf)/noise_var_m, axis=-1), | |||
| axis=-1)*D/2. | |||
| logL = logL + F.sum(F.sum(Linvmu*LinvKufY, axis=-1), axis=-1) | |||
| logL = logL + self.model.U.factor.log_pdf_scaling*KL_u | |||
| logL = self.log_pdf_scaling*logL + KL_u | |||
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Can you add a reference to the doc here (and to the other GP implementations please) about where you get the maths from?
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This relates to mini-batch learning. We should have a tutorial explaining this.
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