Remove slide content where possible, improve overview transitions
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30
index.qmd
30
index.qmd
@@ -173,11 +173,7 @@ col_yellow <- "#FCE135"
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::::
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## Overview of the Thesis {#sec-overview}
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::: {.r-stack}
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::: {.fragment .fade-in-then-out}
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## Overview of the Thesis {#sec-overview transition="fade" transition-speed="slow"}
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<table style="width: 100%; border-collapse: separate; border-spacing: 0 1em; border: none;">
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<tr style="border: none;">
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@@ -238,9 +234,7 @@ col_yellow <- "#FCE135"
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</tr>
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</table>
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:::
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::: {.fragment .fade-in-then-out}
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## Overview of the Thesis {transition="fade" transition-speed="slow" visibility="uncounted"}
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<table style="width: 100%; border-collapse: separate; border-spacing: 0 1em; border: none;">
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<tr style="border: none;">
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@@ -301,9 +295,7 @@ col_yellow <- "#FCE135"
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</tr>
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</table>
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:::
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::: {.fragment .fade-in-then-out}
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## Overview of the Thesis {transition="fade" transition-speed="slow" visibility="uncounted"}
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<table style="width: 100%; border-collapse: separate; border-spacing: 0 1em; border: none;">
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<tr class = "greyed-out" style="border: none;">
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@@ -364,9 +356,6 @@ col_yellow <- "#FCE135"
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</tr>
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</table>
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:::
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:::
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## Overview
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@@ -1730,8 +1719,7 @@ for( t in 1:T ) {
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$\boldsymbol \beta_{t} = K \boldsymbol \beta_{0} \odot \boldsymbol {SoftMax}\left( - \boldsymbol \eta_{t} \odot \boldsymbol R_{t} + \log( \boldsymbol \eta_{t}) \right)$
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$\boldsymbol w_{t}(\boldsymbol P) = \underbrace{\boldsymbol B(\boldsymbol B'\boldsymbol B+ \lambda (\alpha \boldsymbol D_1'\boldsymbol D_1 + (1-\alpha) \boldsymbol D_2'\boldsymbol D_2))^{-1} \boldsymbol B'}_{\boldsymbol{\mathcal{H}}} \boldsymbol B \boldsymbol \beta_{t}$
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}
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<p style="margin:0em;">}</p>
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:::
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@@ -1775,20 +1763,14 @@ Data Generating Process of the [simple probabilistic example](#simple_example):
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## QL Deviation
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Deviation from best attainable QL (1000 runs).
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## CRPS vs. Lambda
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CRPS Values for different $\lambda$ (1000 runs)
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## Knots
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CRPS for different number of knots (1000 runs)
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::::
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@@ -1799,8 +1781,6 @@ CRPS for different number of knots (1000 runs)
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## Comparison to EWA and ML-Poly
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The same simulation carried out for different algorithms (1000 runs):
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<center>
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<img src="assets/crps_learning/algos_constant.gif">
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</center>
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