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Hi Patrick, I see you are using general solvers to solve the least squares problem, [by contructing an objective out of residuals](https://github.com/patrick-kidger/optimistix/blob/main/optimistix/_le…
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I am currently experimenting with a FOSS SQP method, SLSQP, trying to replace the old numerically unstable Lawson-Hanson LSEI solver with a more modern, more reliable QP solver. See: https://github.co…
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I am the main author of "Domain adaptation for regression under Beer–Lambert’s law" and creator of the (unsupervised) domain adaptation extension of partial least squares regression called di-PLS that…
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It seems RLS is a way to reach the same solution as batch linear regression. It's probably more expensive than SGD, but is still interesting.
## Resources
- https://www.wikiwand.com/en/Recursive_lea…
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Thank you for finalizing this @samcoveney.
Overall, I am ok with this PR. Multiple follow up PRs will be needed.
- Tutorial on a new PR
- parallel backend currently not available. …
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Make a least-squares fit with uncertainties to the 9 groups using the code above (1 member due till Wednesday 2pm).
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# High level description
Least squares batch filters and classical Kalman filters are both methods for estimating the state of a dynamic system from noisy measurements. They both use a mathematical…
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Hello, I'm hoping you can help me understand why is the dimension of A TD*N, TD*H, since the dimension of hidden_states is T*D1, it becomes T*D after dense.
ATA += W * (hidden_states @ hidden_st…
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### Is your feature request related to a problem? Please describe.
An old PR, gh-12755, proposed adding a package for Automatically Regularized Least Squares to SciPy. See https://github.com/scipy/…
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https://medium.com/nuances-of-programming/qr-%D1%80%D0%B0%D0%B7%D0%BB%D0%BE%D0%B6%D0%B5%D0%BD%D0%B8%D0%B5-%D0%BC%D0%B0%D1%82%D1%80%D0%B8%D1%86%D1%8B-cf6a84673cbd