Chris Bogan created SPARK-26748:
-----------------------------------
Summary: CLONE - Autoencoder
Key: SPARK-26748
URL: https://issues.apache.org/jira/browse/SPARK-26748
Project: Spark
Issue Type: Improvement
Components: ML
Affects Versions: 1.5.0
Reporter: Chris Bogan
Assignee: Alexander Ulanov
Goal: Implement various types of autoencoders
Requirements:
1)Basic (deep) autoencoder that supports different types of inputs: binary,
real in [0..1]. real in [-inf, +inf]
2)Sparse autoencoder i.e. L1 regularization. It should be added as a feature to
the MLP and then used here
3)Denoising autoencoder
4)Stacked autoencoder for pre-training of deep networks. It should support
arbitrary network layers
References:
1. Vincent, Pascal, et al. "Extracting and composing robust features with
denoising autoencoders." Proceedings of the 25th international conference on
Machine learning. ACM, 2008.
http://www.iro.umontreal.ca/~vincentp/Publications/denoising_autoencoders_tr1316.pdf
2. http://machinelearning.wustl.edu/mlpapers/paper_files/ICML2011Rifai_455.pdf,
3. Vincent, P., Larochelle, H., Lajoie, I., Bengio, Y., and Manzagol, P.-A.
(2010). Stacked denoising autoencoders: Learning useful representations in a
deep network with a local denoising criterion. Journal of Machine Learning
Research, 11(3371–3408).
http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.297.3484&rep=rep1&type=pdf
4, 5, 6. Bengio, Yoshua, et al. "Greedy layer-wise training of deep networks."
Advances in neural information processing systems 19 (2007): 153.
http://www.iro.umontreal.ca/~lisa/pointeurs/dbn_supervised_tr1282.pdf
--
This message was sent by Atlassian JIRA
(v7.6.3#76005)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
