Title | A First Approach to Face Dimensionality Reduction Through Denoising Autoencoders |
Publication Type | Conference Paper |
Year of Publication | 2018 |
Authors | Pulgar-Rubio, F., Charte Francisco, Rivera-Rivas A.J., and del Jesus M. J. |
Conference Name | 19th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2018 |
Pagination | 439–447 |
Date Published | 11 |
Conference Location | Madrid (Spain) |
ISBN Number | 978-3-030-03493-1 |
Abstract | The problem of high dimensionality is a challenge when facing machine learning tasks. A high dimensional space has a negative effect on the predictive performance of many methods, specifically, classification algorithms. There are different proposals that arise to mitigate the effects of this phenomenon. In this sense, models based on deep learning have emerged. |
Notes | TIN2015-68854-R; FPU16/00324 |
DOI | 10.1007/978-3-030-03493-1_46 |
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