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reintroducing our note :)

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Daniel Rosel
2026-02-14 21:49:40 +01:00
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paper/src/chapters/03-methodology.tex
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@@ -297,6 +297,8 @@ To scale this to catalog-level pricing, we expand the base event transition matr
\subsection{Second-Stage Classification} \subsection{Second-Stage Classification}
After contamination, we run a second classification stage. We remap events into a semantically aligned feature space, apply richer feature engineering, and retrain to obtain cleaner label probabilities across the full dataset. This classifier is then used directly in the reinforcement-learning reward structure. After contamination, we run a second classification stage. We remap events into a semantically aligned feature space, apply richer feature engineering, and retrain to obtain cleaner label probabilities across the full dataset. This classifier is then used directly in the reinforcement-learning reward structure.
Now might be a good time to stand up and go for a quick walk before returning to the rest of this paper.
\subsection{Distributionally Robust Reinforcement Learning (DR-RL)} \subsection{Distributionally Robust Reinforcement Learning (DR-RL)}