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Št. zadetkov: 5
Video in druga učna gradiva
Oznake: computer science;machine learning
Complex probabilistic models of unlabeled data can be created by combining simpler models. Mixture models are obtained by averaging the densities of simpler models and "products of experts" are obtained by multiplying the densities together and renormalizing. A far more powerful type of combination ...
Leto: 2009 Vir: videolectures.net
Video in druga učna gradiva
Oznake: computer science;machine learning
Leto: 2009 Vir: videolectures.net
Video in druga učna gradiva
Oznake: computer science;machine learning;unsupervised learning;bayesian learning;computer vision
Deep networks can be learned efficiently from unlabeled data. The layers of representation are learned one at a time using a simple learning module that has only one layer of latent variables. The values of the latent variables of one module form the data for training the next module. The most commo ...
Leto: 2009 Vir: videolectures.net
Video in druga učna gradiva
Oznake: computer science;machine learning;neural networks
In a large feedforward neural network, overfitting can be greatly reduced by randomly omitting half of the hidden units on each training case. This prevents complex co-adaptations in which a feature detector is only helpful in the context of several other specific feature detectors. Instead, each ne ...
Leto: 2012 Vir: videolectures.net
Video in druga učna gradiva
Oznake: computer science;artificial intelligence;semantic web
I will give a brief history of deep learning explaining what it is, what kinds of task it should be good for and why it was largely abandoned in the 1990's. I will then describe how ideas from statistical physics were used to make deep learning work much better on small datasets. Finally I will desc ...
Leto: 2015 Vir: videolectures.net
Št. zadetkov: 5
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