|
You are here |
codethrasher.com | ||
| | | | |
arkadiusz-jadczyk.eu
|
|
| | | | | We continue Becoming anti de Sitter. Every matrix $\Xi$ in the Lie algebra o(2,2) generates one-parameter group $e^{\Xi t}$ of linear transformations of $\mathbf{R}^4.$ Vectors tangent to orbits of this group form a vector field. Let us find the formula for the vector field generated by $\Xi. | |
| | | | |
www.math3ma.com
|
|
| | | | | ||
| | | | |
adam.younglogic.com
|
|
| | | | | [AI summary] The article discusses an algorithm for parallelizing matrix-vector multiplication by decomposing the computation into smaller chunks to enable parallel processing. | |
| | | | |
blog.georgeshakan.com
|
|
| | | Principal Component Analysis (PCA) is a popular technique in machine learning for dimension reduction. It can be derived from Singular Value Decomposition (SVD) which we will discuss in this post. We will cover the math, an example in python, and finally some intuition. The Math SVD asserts that any $latex m \times d$ matrix $latex... | ||