Online Incremental Feature Learning with Denoising Autoencoders

  title={Online Incremental Feature Learning with Denoising Autoencoders},
  author={Guanyu Zhou and Kihyuk Sohn and Honglak Lee},
While determining model complexity is an important problem in machine learning, many feature learning algorithms rely on cross-validation to choose an optimal number of features, which is usually challenging for online learning from a massive stream of data. In this paper, we propose an incremental feature learning algorithm to determine the optimal model complexity for large-scale, online datasets based on the denoising autoencoder. This algorithm is composed of two processes: adding features… CONTINUE READING
Highly Cited
This paper has 88 citations. REVIEW CITATIONS

5 Figures & Tables



Citations per Year

89 Citations

Semantic Scholar estimates that this publication has 89 citations based on the available data.

See our FAQ for additional information.