Hari
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Algorithm for optimizing Ax = b with unknown A and known x values
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9 votes

Your problem sounds like Independent Component Analysis. Where $x_i$ are the measurements in which the source signals have got mixed and $b_i$ are the values emitted by the sources. The $A$ in your ...

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Would recalculating the residual in the conjugate gradient method help?
3 votes

This tutorial talks about recalculating the residual every 50 iterations to mitigate round-off errors.

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How do I correctly multiply vectors and matrices in Python and MATLAB?
Accepted answer
3 votes

David Ketcheson has already indicated the problem in his comment. I will flesh it out here. Note the form of the argument of the log in the logistic regression objective: $log[1+exp(−b_iA^T_ix)]$ ...

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Levenberg-Marquardt - What is preferable (A + mu.I) or (A + mu.diag[A])?
0 votes

The form $(A+μdiag(A))h=−g$ can be used always and it gives better results than $(A+μI)h=−g$ in practice. The reason given by the OP is right. It moves faster along flatter directions in error valleys ...

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Minimisation problem in thousands of dimensions
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I suppose your problem (log-likelihood from a Potts model) is convex. For very large scale problems, using Hessian (second order) information may not be scalable and/or efficient. There is a growing ...

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