
Explainable machine learning (XAI) is an essential technique for creating machine learning models that are transparent, unbiased, and
Explainable machine learning (XAI) is an essential technique for creating machine learning models that are transparent, unbiased, and
Optimization_Problem_8 Problem Derive the precondition conjugate gradient by applying the standard conjugate gradient in the variables $hat{x}$ and
Optimization_Problem_7 Problem Show that the newton method applied to $r(x) = -x^5 + x^3 + 4x$ where the
Optimization_Problem_6 Problem Using $beta_k = frac{r_k^TAp_{k-1}}{p_{k-1}^TAp_{k-1}}$ verify that $ span[r_0, …, r_k] = span[Ar_0, …, A^kr_0] $ and
Optimization_Problem_4 Problem Given a point $x_k in mathbb{R}^n$, a function f(x) $ in mathbb{R}^n$, a NxN symmetrix matrix,
Intro_to_GAN_NN_2 Now that we have a basic understanding of the underlying background of building a NN, lets talk
Untitled This introduction is assuming you have a basic understanding of Neural Networks, activation functions, and the likes.
My friends have described me in a bunch of ways that make me go hmmmm. Here is the
Optimization_Problem_5 Problem Show the one dimensional minimizer of a strong convex quadrative function Solution: State the quadractic function:
Numerical Optimization Chapter 3 Line Search Methods¶ As previously stated the calculation of the next step is mathematically