AI News, Artificial Neural Networks/Competitive Learning

Artificial Neural Networks/Competitive Learning

Competitive learning is a rule based on the idea that only one neuron from a given iteration in a given layer will fire at a time.

The “winner” of each iteration, element i* , is the element whose total weighted input is the largest.

Neurons become trained to be individual feature detectors, and a combination of feature detectors can be used to identify large classes of features from the input space.

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How to Generate Art - Intro to Deep Learning #8

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Lecture 3 | Loss Functions and Optimization

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Lecture 05 - Training Versus Testing

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f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization, NIPS 2016

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How to Make an Image Classifier - Intro to Deep Learning #6

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Lecture 12 - Regularization

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Lecture 14 | Deep Reinforcement Learning

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Lecture 10 | Recurrent Neural Networks

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