Papers: Difference between revisions
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* [[File: 2_The_Derivative_Rules.pdf]] | * [[File: 2_The_Derivative_Rules.pdf]] | ||
In 1979 Ken Iverson wrote a paper on the derivative as part of the ACM APL Conference. That paper included a section summarizing the rules for the derivatives of compound formulations such as f×g. His summary omits the derivation of these rules. This article aims to restate these rules in more modern notation and provide derivations for Iverson's results. [[Mike Powell]] | In 1979 Ken Iverson wrote a paper on the derivative as part of the ACM APL Conference. That paper included a section summarizing the rules for the derivatives of compound formulations such as f×g. His summary omits the derivation of these rules. This article aims to restate these rules in more modern notation and provide derivations for Iverson's results. [[Mike Powell]] | ||
* [[File: 3_Machine_Learning.pdf]] | |||
This tutorial explores the pattern recognition model for handwritten digits using data from the Modified National Institute of Standards and Technology database. It focuses on deriving the analytic gradients in APL and establishing them as part of the back propagation algorithm. | |||
{{APL community}} | {{APL community}} | ||
Revision as of 19:39, 7 April 2020
This is a list of repositories of external papers, as well as stand-alone papers not part of a collection.
Eventually, they should be categorised.
- Sudley Place Bob Smith
- Jsoftware Roger Hui
- keiapl.org
- Dyalog external publications
- Software Preservation Group (subfolders in sidebar)
- APL-J Language Donald McIntyre
- Articles and APL Chronology (timeline with links) from SIGAPL
- A Personal History of APL by Michael S. Montalbano
- File:1 The Derivative Revisited.pdf
A fresh look at Ken Iverson's 1979 paper "The Derivative Operator" Mike Powell
In 1979 Ken Iverson wrote a paper on the derivative as part of the ACM APL Conference. That paper included a section summarizing the rules for the derivatives of compound formulations such as f×g. His summary omits the derivation of these rules. This article aims to restate these rules in more modern notation and provide derivations for Iverson's results. Mike Powell
This tutorial explores the pattern recognition model for handwritten digits using data from the Modified National Institute of Standards and Technology database. It focuses on deriving the analytic gradients in APL and establishing them as part of the back propagation algorithm.
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