Myriam  Rogahn

Myriam Rogahn

1598625780

Quickprop, an Alternative to Back-Propagation

Due to the slowly converging nature of the vanilla back-propagation algorithms of the ’80s/’90s, Scott Fahlman invented a learning algorithm dubbed Quickprop [1] that is roughly based on Newton’s method. His simple idea outperformed back-propagation (with various adjustments) on problem domains like the ‘N-M-N Encoder’ task — i.e. training a de-/encoder network with N inputs, M hidden units and N outputs.

One of the problems that Quickprop specifically tackles is the issue of finding a domain-specific optimal learning rate, or rather: an algorithm that adjusts it appropriately dynamically.

In this article, we’ll look at the simple mathematical idea behind Quickprop. We’ll implement the basic algorithm and some improvements that Fahlman suggests — all in Python and PyTorch.

A rough implementation of the algorithm and some background can already be found in this useful blog post by Giuseppe Bonaccorso. We are going to expand on that — both on the theory and code side — but if in doubt, have a look at how Giuseppe explains it.


The motivation to look into Quickprop came from writing my last article on the “Cascade-Correlation Learning Architecture” [2]. There, I used it to train the neural network’s output and hidden neurons, which was a mistake I realized only later and which we’ll also look into here.

To follow along with this article, you should be familiar with how neural networks can be trained using back-propagation of the loss gradient (as of 2020, a widely used approach). That is, you should understand how the gradient is usually calculated and applied to the parameters of a network to try to iteratively achieve convergence of the loss to a global minimum.


Overview

We’ll start with the mathematics behind Quickprop and then look at how it can be implemented and improved step by step.

To make following along easier, any equations used and inference steps done are explained in more detail than in the original paper.

The Mathematics Behind Quickprop

The often used learning method of back-propagation for neural networks is based on the idea of iteratively ‘riding down’ the slop of a function, by taking short steps in the inverse direction of its gradient.

These ‘short steps’ are the crux here. Their length usually depends on a learning rate factor, and that is kept intentionally small to not overshoot a potential minimum.

#python #pytorch #quickprop #artificial-intelligence #machine-learning

What is GEEK

Buddha Community

Quickprop, an Alternative to Back-Propagation
Myriam  Rogahn

Myriam Rogahn

1598625780

Quickprop, an Alternative to Back-Propagation

Due to the slowly converging nature of the vanilla back-propagation algorithms of the ’80s/’90s, Scott Fahlman invented a learning algorithm dubbed Quickprop [1] that is roughly based on Newton’s method. His simple idea outperformed back-propagation (with various adjustments) on problem domains like the ‘N-M-N Encoder’ task — i.e. training a de-/encoder network with N inputs, M hidden units and N outputs.

One of the problems that Quickprop specifically tackles is the issue of finding a domain-specific optimal learning rate, or rather: an algorithm that adjusts it appropriately dynamically.

In this article, we’ll look at the simple mathematical idea behind Quickprop. We’ll implement the basic algorithm and some improvements that Fahlman suggests — all in Python and PyTorch.

A rough implementation of the algorithm and some background can already be found in this useful blog post by Giuseppe Bonaccorso. We are going to expand on that — both on the theory and code side — but if in doubt, have a look at how Giuseppe explains it.


The motivation to look into Quickprop came from writing my last article on the “Cascade-Correlation Learning Architecture” [2]. There, I used it to train the neural network’s output and hidden neurons, which was a mistake I realized only later and which we’ll also look into here.

To follow along with this article, you should be familiar with how neural networks can be trained using back-propagation of the loss gradient (as of 2020, a widely used approach). That is, you should understand how the gradient is usually calculated and applied to the parameters of a network to try to iteratively achieve convergence of the loss to a global minimum.


Overview

We’ll start with the mathematics behind Quickprop and then look at how it can be implemented and improved step by step.

To make following along easier, any equations used and inference steps done are explained in more detail than in the original paper.

The Mathematics Behind Quickprop

The often used learning method of back-propagation for neural networks is based on the idea of iteratively ‘riding down’ the slop of a function, by taking short steps in the inverse direction of its gradient.

These ‘short steps’ are the crux here. Their length usually depends on a learning rate factor, and that is kept intentionally small to not overshoot a potential minimum.

#python #pytorch #quickprop #artificial-intelligence #machine-learning

Hubify Apps

Hubify Apps

1614420140

Back In Stock Notification App for Your Shopify Store

The last thing you want to do is to dissatisfy your customers. It is quite disappointing for online shoppers to want to purchase a product and they end up discovering that it is out of stock.

One thing that is common among Shopify stores is that they usually experience stockouts. A stockout occurs when inventory gets finished. If customers want to handle issues concerning stock outs effectively, then, they should use Shopify product back-in-stock alerts App.

What can back in stock alerts help you do? It can help customers notify shoppers when products are available if they subscribe to it using the back in stock notification app.

Learn More : https://hubifyapps.com/back-in-stock-notification-app/

#back in stock notification app #back in stock alert #in stock alert #in stock #back in stock #stock alert app

Marcus Anthony

1615377252

Dream11 Clone | Dream11 Clone App | Fantasy Sports App like Dream11

No matter what age group you belong to or which sport you love. When your favorite team or favorite player is out there in the field, a true fan can never stay away. This craze was turned into cash by the fans in the earlier days under the name sports betting.

Why choose Dream11 out of all the other apps?

Though it ended up in many unfortunate situations for the participants of it, it is now turning into something more profitable nowadays. This is because of apps like Dream11. Founded in 2008 before the IPL, the company raked in billions of dollars. All thanks to the cricket fans who showered their immense love for their teams and players. And the success that it started to see then, has still not simmered down, as it is offering options to the users to participate in different tournaments.

Development of Dream11 Clone

Developing such an app is not rocket science. But whether it is a cakewalk or not depends on which method you want to implement to develop a fantasy sports app. If you choose to develop it from scratch, let’s say that it’s going to take half of your lifetime. But when you choose a ready-made solution, then development is just a breeze. Because it is ready-made, still you can make changes, and you can launch. The app will also contain some basic features.

Listed below are them.

Fundamental features

User panel
User login
Home screen
League arena
User dashboard

Admin panel

Admin dashboard
Manage user accounts
Manage reports

Conclusion
So if you are ready and are curious about knowing more about the Dream11 like app development, then ping us now!

#dream11 clone #dream11 app clone #dream11 like app #dream11 alternative #dream11 alternative solution #alternative to dream11

Marcus Anthony

1626325881

Set Your March To The Mobile Wallet Market With An App Like Freecharge

Mobile wallets like Freecharge help out people with fund transfers and bill payments. Through Freecharge, the users can make their mobile recharges, telephone bills, and other utility bills like electricity bills, gas bills, DTH recharges, and many more. Would you like to start your venture with a similar app like Freecharge? Then, a Freecharge clone will be the best option to start your career.

What is a Freecharge clone app?

Mobile wallets like Freecharge help out people with fund transfers and bill payments. Through Freecharge, the users can make their mobile recharges, telephone bills, and other utility bills like electricity bills, gas bills, DTH recharges, and many more. The Freecharge clone app is a similar app developed with the same models and features as the standard app.

You can opt for a ready-to-launch Freecharge clone app with which you can launch your business in no time. Make sure to have the following features in your app. Mobile wallets like Freecharge help out people with fund transfers and bill payments. Would you like to start your venture with a similar app like Freecharge? Then, a Freecharge clone will be the best option to start your career.

User registration

The Freecharge clone app offers an easy registration process for the users to register with their app. They can quickly log in through their credentials like email address, phone number, or through their social media account.

Linking bank account

Through a secure SMS verification process, the users can easily link their bank account to the Freecharge clone app.

QR scan code

The users can scan through the QR code of their service provider and transfer the amount to their account in the blink of an eye.

Push notifications

The Freecharge clone app will send important notifications and alert messages to its users through SMS. Like their credit or debit status, their account summary will be intimated to the users through notifications.

Summing up,

In this digital era, mobile wallets have become the best medium for people to transact their funds. In this scenario, you can enter the mobile wallet market swiftly by launching a Freecharge clone app.

#alternative to freecharge #freecharge alternative solution #freecharge alternative #freecharge like app development #app like freecharge

Scott Rollins

1613655769

Uber Alternative | On-demand Uber Alternative App Solution

The market leader Appdupe helps entrepreneurs make an everlasting presence in the on-demand taxi sector with a leading-edge Uber alternative. The taxi clone app stands apart from the rest with its feature-packed front-end and efficient dispatcher algorithm. The pragmatic solution helps entrepreneurs regulate their fleet community efficiently without tearing a sweat.

As a measure to tackle COVID-19, the platform comes preloaded with safety add-ons like face mask recognition software, safety ratings & reviews, etc. The best part about the solution is that it can be tweaked to suit your business needs seamlessly.

Some of the pivotal features of the Uber alternative solution include,

  • Free app updation for lifetime
  • Geofencing
  • VoIP-based call masking
  • Multilingual & Multi-currency support
  • In-app wallet
  • KIOSK booking app
  • Multiple stop points
  • ‘Book For Others’ Feature

Know more about Uber alternative, https://www.appdupe.com/uber-for-x-clone-script

Contact us through +91 9791101817 or mail info@appdupe.com

#uber alternative, uber alternative app, on-demand uber alternative app solution