Firefly documentation - #31
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Pull request overview
This PR substantially expands the Firefly algorithm documentation to better explain Firefly as an iterative local “neural architecture descent” method, and to clarify how width and depth growth are performed and selected.
Changes:
- Replaces the brief Firefly description with a fuller conceptual overview (objective, local neighborhood, and selection procedure).
- Adds detailed explanations (with equations) for width growth (splits + new neurons) and depth growth (residual-layer insertion).
- Adds an “Experimental results” section with a referenced figure and summarized takeaways.
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| 1. Over-grow and optimize | ||
| ~~~~~~~~~~~~~~~~~~~~~~~~~ | ||
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| 2. Score and select candidates | ||
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ | ||
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| .. math:: | ||
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| f_{t+1}=\arg\min_f L(f) |
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| [\tilde{\boldsymbol{\epsilon}},\tilde{\boldsymbol{\delta}}] | ||
| =\arg\min_{\boldsymbol{\epsilon},\boldsymbol{\delta}} | ||
| L(f_{\boldsymbol{\epsilon},\boldsymbol{\delta}}) |
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| \hat{\boldsymbol{\epsilon}} | ||
| =\arg\min_{\boldsymbol{\epsilon}}\sum_i\epsilon_i s_i |
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Summary