Fixes for structured LBFGS approximation.#38
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lambe wants to merge 5 commits intoPythonOptimizers:developfrom
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Fixes for structured LBFGS approximation.#38lambe wants to merge 5 commits intoPythonOptimizers:developfrom
lambe wants to merge 5 commits intoPythonOptimizers:developfrom
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added 5 commits
December 13, 2016 16:05
The function now produces the same result as the other LBFGS approximations when y and yd are identical vectors.
warnings about negative values in the square root and changed the step acceptance threshold to be more permissive.
Collaborator
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Could you please somehow add a test that verifies the correctness of this? Perhaps by comparing to a full BFGS update on a small examples (3 or 4 variables)? |
dpo
reviewed
Mar 30, 2017
| ad[:, k] += update.copy() | ||
| aTsk = np.dot(a[:, l], s[:, k]) | ||
| adTsk = np.dot(ad[:, l], s[:, k]) | ||
| aTsl = np.dot(a[:, l], s[:, l]) |
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Wasn't this already computed in aTs[l]?
dpo
reviewed
Mar 30, 2017
| update = (aTsk / aTsl) * ad[:, l] + (adTsk / aTsl) * a[:, l] - \ | ||
| (aTsk * adTsl / aTsl**2) * a[:, l] | ||
| a[:, k] -= update.copy() | ||
| ad[:, k] -= update.copy() |
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Why these changes? It's hard to tell whether they actually modify the behavior or are just a rewrite.
Author
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If I remember correctly, it's just a rewrite to make the similarity between structured LBFGS and structured LSR1 obvious.
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Ok. In that case, it's wasteful to recompute the dot products that are already stored in aTs.
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