# Least Squares

This is basically Line of Best Fit.

Saw this in the Kalman Filter book.

https://numpy.org/doc/stable/reference/generated/numpy.polyfit.html

Learning more seriously from Cyrill Stachniss in the context of SLAM.

Resources

Least Squares vs. SVD?

SVD (Singular Value Decomposition): A mathematical technique for factorizing a matrix into three separate matrices. Used in various applications, including dimensionality reduction, noise reduction, and solving linear equations.

Least Squares: A method for estimating the coefficients in a linear regression model. Minimizes the sum of the squared differences between observed and predicted values.

### Non-Linear Least Squares

Found from a quick google search https://github.com/Rookfighter/least-squares-cpp

Options to solve:

- Ceres Solver http://ceres-solver.org/
- G2o https://github.com/RainerKuemmerle/g2o
- Eigen?
- Sophus
- CuSOLVER https://docs.nvidia.com/cuda/cusolver/index.html#using-the-cusolver-api