We extend the ideas of from Automatic Differentiation with Scala to include the reverse accumulation. Reverse accumulation is a non-obvious improvement to automatic differentiation that can in many cases vastly speed up calculations of gradients. Read more…
Categories: Applications, Coding, Exciting Techniques, Mathematics, Programming, Tutorials Tags: Automatic Differentiation, Conjugate Gradient, Gradient, Mathematical Bedside Reading, Optimization, Reverse Accumulation, Scala
This article is a worked-out exercise in applying the Scala type system to solve a small scale optimization problem. For this article we supply complete Scala source code (under a GPLv3 license) and some design discussion. Read more…
Categories: Applications, Coding, Computer Science, Exciting Techniques, Mathematics, Programming, Tutorials Tags: Automatic Differentiation, Conjugate Gradient, Dual Numbers, Geometric Median, Numeric Methods, Optimization, Scala, Steiner Tree
Readers returning to our blog will know that Win-Vector LLC is fairly “pro-R.” You can take that to mean “in favor or R” or “professionally using R” (both statements are true). Some days we really don’t feel that way. Read more…
One of my research interests is finding the principles that underly the management of information, complexity and uncertainty. When something as simple as a web-form is called “technology” it is time to step back and examine your principles. One principle I am not sure about Postel’s law. It doesn’t hold often enough to be relied on and when it fails I am not sure who to be angry with. Read more…
This article is quick concrete example of how to use the techniques from Survive R to lower the steepness of The R Project for Statistical Computing‘s learning curve (so an apology to all readers who are not interested in R). What follows is for people who already use R and want to achieve more control of the software. Read more…