Update README.md

README.md

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 {}
 ---
 
+**Curated by:** [Andrew Rosemberg & Contributors]
+
 # Dataset Card for Parametric Optimization Problems
 
 <!-- Provide a quick summary of the dataset. -->
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 \end{aligned}
 $$
 
-where \\( \theta \\) is the parameter. In different fields, these parameters go by different names:
-
-1. Hyperparameters in machine learning
-2. Risk aversion or other backtesing parameters in financial modelling
-3. Parameterized systems in control theory
-
-**Key Features:**
-- **Parametrized Constraints**: The parameters appear as variables in the `function` part of a constraint, with the constraint `set` field set to `"Parameter"`.
-- **Consistent JSON Structure**: This ensures straightforward programmatic parsing, enabling large-scale experimentation with solvers or ML-based proxies.
-
-- **Curated by:** [Andrew Rosemberg & Contributors]
+where \\( \theta \\) is the parameter.
 
 ## Usage