Neural network, Neural networks, Machine learning, Unsupervised learning, Supervised learning, Artificial intelligence

Gradient-based Learning Applied To Document Recognition - Proceedings of the IEEE

On Nov 1, 2020
@MIT_CSAIL shared
#otd in 1998 Yann LeCun submitted a paper on “gradient-based” deep learning for document recognition. It took more than a decade before the world finally warmed to neural networks: https://t.co/oNInoVlvHl https://t.co/JJ39ko8BLQ
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Keywords— Convolutional neural networks, document recog- nition, finite state transducers, gradient-based learning, graph transformer networks, machine learning, neural networks, optical character recognition (OCR). For example, a document recognition system is composed of a field loca- ...

pdfs.semanticscholar.org
On Nov 1, 2020
@MIT_CSAIL shared
#otd in 1998 Yann LeCun submitted a paper on “gradient-based” deep learning for document recognition. It took more than a decade before the world finally warmed to neural networks: https://t.co/oNInoVlvHl https://t.co/JJ39ko8BLQ
Open

Gradient-based Learning Applied To Document Recognition - Proceedings of the IEEE

Gradient-based Learning Applied To Document Recognition - Proceedings of the IEEE

Keywords— Convolutional neural networks, document recog- nition, finite state transducers, gradient-based learning, graph transformer networks, machine learning, neural networks, optical ...

Book: Machine Learning: a Probabilistic Perspective

Book: Machine Learning: a Probabilistic Perspective

Today’s Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automa…

8 Tricks for Configuring Backpropagation to Train Better Neural Networks

8 Tricks for Configuring Backpropagation to Train Better Neural Networks

Neural network models are trained using stochastic gradient descent and model weights are updated using the backpropagation algorithm. The optimization solved by training a neural network ...

Glossary

Glossary

Definitions of various technical terms in artifical intelligence.

An Overview of Deep Learning for Curious People

An Overview of Deep Learning for Curious People

Starting earlier this year, I grew a strong curiosity of deep learning and spent some time reading about this field. To document what I’ve learned and to pro...

What is deep learning? Algorithms that mimic the human brain

What is deep learning? Algorithms that mimic the human brain

Deep neural networks can solve the most challenging problems, but require abundant computing power and massive amounts of data

Click here to read the article

Click here to read the article

A Lagrangian Method for Inverse Problems in Reinforcement Learning Pierre-Luc Bacon Department of Computer Science Stanford University [email protected] Florian Schäfer Computing and ...

Artificial Intelligence and Deep Learning For the Extremely Confused

Artificial Intelligence and Deep Learning For the Extremely Confused

The watershed moment in Deep Learning is typically cited as 2012’s AlexNet, by Alex Krizhevsky and Geoffrey Hinton, a state of the art GPU accelerated Deep Learning network that won that ...

MetaInit: Initializing learning by learning to initialize

MetaInit: Initializing learning by learning to initialize

MetaInit: Initializing learning by learning to initialize Yann N. Dauphin Google AI [email protected] Samuel S. Schoenholz Google AI [email protected] Abstract Deep learning models frequently ...