A lot of my ideas about Machine Learning come from Quantum Mechanical Perturbation Theory. To provide some context, we need to step back and understand
Author: Charles H Martin, PhD
Machine Learning Enthusiast and Consultant
Kernels, Green’s Functions, and Resolvent Operators
Machine Learning uses Kernels. At least it tries when it can. A Kernel is an operator on a Hilbert Space. Or we might say that
Eigenvalue-Independent Effective (Semantic) Operator
This post is still just sketch of ideas…not ready for consumption In my last post I introduced the Eigenvalue-Dependent Effective (Semantic) Operator as a Semantic Similarity
Effective Operators for Eigenvalues and Clustering
I a previous post, I introduced the Effective Regression Operator for supervised (and semi-supervised) Machine Learning problems. Here, I will introduce a different Effective Operator,
Effective Operators part 2: Simple SemiSupervised Learning
We consider a very common example of Machine Learning problem as an application to the Effective Operator Framework: Simple SemiSupervised Learning Suppose we have N
Kernels and Quantum Gravity Part 3: Coherent States
This would not be a pedagogic machine learning blog if I did not go into some overly abstract formalism…here we introduce the Kernel formalism using
