Distinct Feature Learning and Nonlinear Variation Pattern Discovery Using Regularized Autoencoders
abstract: Feature learning and the discovery of nonlinear variation patterns in high-dimensional data is an important task in many problem domains, such as imaging, streaming data from sensors, and manufacturing. This dissertation presents several methods for learning and visualizing nonlinear varia...
| Other Authors: | |
|---|---|
| Format: | Doctoral Thesis |
| Language: | English |
| Published: |
2016
|
| Subjects: | |
| Online Access: | http://hdl.handle.net/2286/R.I.38620 |