Training Restricted Boltzmann Machines

By Asja Fischer. 2015

40 citations recorded by the source corpus.

Subfields: Computational Mechanics, Computer Vision and Pattern Recognition, Statistical and Nonlinear Physics

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

1. Sherif Sakr
2. Radwa El Shawi
3. Mohamed Maher

In Statistical and Nonlinear Physics

1. Sherif Sakr
2. Radwa El Shawi
3. Mohamed Maher

Citations in the corpus

• Automated Machine Learning: State-of-The-Art and Open Challenges (2019, background): “However, some other solutions depends on different types of auto encoder, Restricted Boltzmann Machines (RBM), [40] by feeding the data features directly to a deep neural networks that can figure out the best features which can be generated using stochastic artificial neural networks that can learn ”