NeurIPS 2015poster2042 citations
Semi-supervised Learning with Ladder Networks
Antti Rasmus, Mathias Berglund, Mikko Honkala, Harri Valpola, Tapani Raiko
Abstract
We combine supervised learning with unsupervised learning in deep neural networks. The proposed model is trained to simultaneously minimize the sum of supervised and unsupervised cost functions by backpropagation, avoiding the need for layer-wise pre-training. Our work builds on top of the Ladder network proposed by Valpola (2015) which we extend by combining the model with supervision. We show that the resulting model reaches state-of-the-art performance in semi-supervised MNIST and CIFAR-10 classification in addition to permutation-invariant MNIST classification with all labels.
BibTeX
@inproceedings{NIPS2015_378a063b,
author = {Rasmus, Antti and Berglund, Mathias and Honkala, Mikko and Valpola, Harri and Raiko, Tapani},
booktitle = {Advances in Neural Information Processing Systems},
editor = {C. Cortes and N. Lawrence and D. Lee and M. Sugiyama and R. Garnett},
pages = {},
publisher = {Curran Associates, Inc.},
title = {Semi-supervised Learning with Ladder Networks},
url = {https://proceedings.neurips.cc/paper_files/paper/2015/file/378a063b8fdb1db941e34f4bde584c7d-Paper.pdf},
volume = {28},
year = {2015}
}