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When optimising parameters of varying scale, we overshoot acceptable parameter ranges during fitting (for non-bounded methods). Transforming / normalising the parameter space on input to the optimiser should solve this issue. An example of this issue is:
Our implementation of Gradient Descent (#88) is unbounded and immediately select a candidate solution orders of magnitude higher than an acceptable range.
Motivation
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Possible implementation
No response
Additional context
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The text was updated successfully, but these errors were encountered:
Feature description
When optimising parameters of varying scale, we overshoot acceptable parameter ranges during fitting (for non-bounded methods). Transforming / normalising the parameter space on input to the optimiser should solve this issue. An example of this issue is:
Our implementation of Gradient Descent (#88) is unbounded and immediately select a candidate solution orders of magnitude higher than an acceptable range.
Motivation
No response
Possible implementation
No response
Additional context
No response
The text was updated successfully, but these errors were encountered: