Additional information

The following references have been used in order to develop LibDEEP techniques:

[1] Hinton, Geoffrey. "A practical guide to training restricted Boltzmann machines." Momentum 9.1, (2010): 926.

[2] Yosinski, Jason, and Hod Lipson. "Visually debugging restricted boltzmann machine training with a 3d example." Representation Learning Workshop, 29th International Conference on Machine Learning, 2012.

[3] Li, Guoqi, et al. "Temperature based Restricted Boltzmann Machines." Scientific reports 6, (2016).

[4] Srivastava, Nitish, et al. "Dropout: a simple way to prevent neural networks from overfitting." Journal of Machine Learning Research 15.1, (2014): 1929-1958.

[5] Wan, Li, et al. "Regularization of neural networks using dropconnect." Proceedings of the 30th International Conference on Machine Learning (ICML-13), (2013).

[6] Larochelle, Hugo, and Yoshua Bengio. "Classification using discriminative restricted Boltzmann machines." Proceedings of the 25th international conference on Machine learning ACM, 2008.

[7] Larochelle, Hugo, et al. "Learning algorithms for the classification restricted boltzmann machine." Journal of Machine Learning Research 13, Mar (2012): 643-669.

[8] Salakhutdinov, Ruslan, and Geoffrey E. Hinton. "Deep Boltzmann Machines." AISTATS Vol. 1, (2009).

[9] Hinton, Geoffrey E. "Deep belief networks." Scholarpedia 4.5, (2009): 5947.

[10] Ahmadlou, Mehran, and Hojjat Adeli. "Enhanced probabilistic neural network with local decision circles: A robust classifier." Integrated Computer-Aided Engineering 17.3, (2010): 197-210.

[11] Abdi, Hervé, and Lynne J. Williams. "Principal component analysis." Wiley Interdisciplinary Reviews: Computational Statistics 2.4, (2010): 433-459.