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- Improve k-means, see [1]
- Get GMM to work on real-world Example
[1] P. S. Bradley, U. Fayyad, Refining Initial Points for K-Means Clustering, in: Proc. of the 15th Int. Conf. on
Machine Learning, 1998, pp. 91–99.
# Least-Squares Lack of User Specified Weighting Vector
- Useful for robustified optimization
# Dogleg Methods
If the matrix is not positive definite then it converges very slowly. Potential solutions involve:
- LDL with D being augmented to ensure it can be solved
- Look into Ceres solver and see how it handles this situation
* Code comments mention solving a dampened system with a regular solver
* This is a bit like a hybrid of LM and TR
# L-BFGS
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